Readability Formulas Explained: Which One to Use?

What Are Readability Formulas? A Brief History of Measuring Reading Difficulty

You've probably pasted text into a tool, seen a score pop up, and thought: what does this number actually mean, and should I trust it? That confusion is completely reasonable, because most people are handed readability scores without any explanation of where they come from or what they're designed to measure. Getting the readability formulas explained properly makes a real difference in how you write for your audience.

Readability research didn't start with software. It started in classrooms. In the 1920s and 1930s, educational researchers like Lively and Pressey were trying to solve a practical problem: textbooks were consistently too difficult for the students who were supposed to read them. Teachers needed a way to objectively measure whether a book was appropriate for a particular grade level, and doing that subjectively was slow and inconsistent.

The first widely adopted formula came from Rudolf Flesch in 1948. Flesch's core insight was simple but powerful: longer words and longer sentences make text harder to read. He quantified that relationship mathematically, and suddenly teachers and publishers had a tool. Not a perfect tool, but a repeatable one. Edgar Dale and Jeanne Chall followed with their formula in 1948 as well, taking a different approach by comparing words against a list of familiar terms known to fourth graders. Robert Gunning introduced his Fog Index in 1952, targeting the business world with a focus on "complex" polysyllabic words. The Coleman-Liau Index appeared in 1975, and the SMOG Index came from G. Harry McLaughlin in 1969, specifically designed to predict comprehension in health and safety materials.

What all these formulas share is a focus on surface-level features of text: word length, sentence length, syllable counts, or character counts. None of them can measure whether a metaphor lands, whether an explanation is logically coherent, or whether the reader actually cares about the topic. That's an important limitation to keep in mind.

Here's the thing though: surface features do correlate with difficulty. Research consistently shows correlations around 0.7 between formula scores and tested comprehension. That's not perfect, but it's good enough to be a useful signal. As Accendo Reliability noted in 2023, readability formulas "assume longer words and sentences equal harder text, but context and audience matter more." That's a fair warning. Use these formulas as a guide, not a verdict.

One more thing before we get into the specifics. A landmark 2023 study published in JAMA Network Open found that the same piece of text could produce scores varying by up to 12.9 grade levels across eight different readability tools, even when those tools claimed to use the same formula. That's not a small discrepancy. It happens because different tools handle punctuation, abbreviations, and sentence boundaries differently. We'll come back to this finding several times, because it's genuinely important for anyone who relies on these scores professionally.

Flesch Reading Ease and Flesch-Kincaid Grade Level Explained

These two formulas are often confused for each other, and that confusion leads people to misinterpret their results. They share the same inputs but produce very different outputs. Let's break them apart.

Flesch Reading Ease produces a score on a 0 to 100 scale. Higher scores mean easier text. The formula is: 206.835 - (1.015 × average sentence length) - (84.6 × average syllables per word). A score between 60 and 70 is considered standard, roughly equivalent to 8th or 9th grade reading level, which is where most popular newspapers aim. A score above 80 is easy reading, suitable for a general consumer audience. Below 30 is very difficult, which is typical of academic journals and legal documents.

Here's a quick reference for interpreting Flesch Reading Ease scores:

90–100: Very easy. Understood by an average 11-year-old. Think children's books and simple instructions.
70–90: Easy. Conversational English. Most consumer-facing web copy aims here.
60–70: Standard. Newspapers and general-interest magazines.
50–60: Fairly difficult. Some college-level content.
30–50: Difficult. Academic writing, technical reports.
0–30: Very difficult. Legal briefs, scientific research.

Flesch-Kincaid Grade Level uses the same inputs but maps them to U.S. school grades instead. The formula is: (0.39 × average sentence length) + (11.8 × average syllables per word) - 15.59. A result of 8.0 means an 8th grader should be able to read the text comfortably. A result of 12.0 means high school senior level.

When is Flesch-Kincaid the best choice? It's ideal for general-purpose content, educational materials, website copy, and marketing writing. It's also the formula embedded in Microsoft Word, which means a huge number of content teams are already using it whether they realize it or not. I've found it works well as a starting point for blog posts and landing pages because the grade level output is easy to communicate to clients or editors who aren't familiar with readability concepts.

The common mistake here is treating the grade level as a ceiling rather than a target. Writing at an 8th-grade level doesn't mean you're dumbing down your content. Research from the National Assessment of Adult Literacy consistently shows that the average American adult reads comfortably at a 7th to 8th grade level. Targeting that range is accurate, not condescending.

One limitation worth knowing: Flesch-Kincaid can underpenalize jargon. A sentence full of three-syllable technical terms might score better than it should if those sentences happen to be short. "Administer subcutaneous injections carefully" is short, so it scores reasonably well, even though "subcutaneous" is going to trip up most readers who aren't medical professionals. This is where pairing Flesch-Kincaid with another formula becomes valuable.

Gunning Fog Index: Reading Levels for Business Writing

Robert Gunning developed the Fog Index specifically because he was frustrated with how difficult business writing had become. He worked with newspapers and corporations in the 1950s and found that executives were producing documents that their own employees couldn't easily understand. His formula was designed to be straightforward enough that writers could apply it without a computer.

The Gunning Fog formula works like this: 0.4 × (average sentence length + percentage of complex words). The result is a U.S. grade level. What makes this formula different is its definition of "complex words": any word with three or more syllables, excluding proper nouns, compound words made from shorter words (like "bookkeeper"), and common suffixes like -ed or -ing that push a word over two syllables. So "complicated" counts as complex, but "swimming" does not.

Ideal Fog scores depend heavily on your audience:

Score 6–8: Easy. Good for consumer newsletters, simple instructions, internal memos.
Score 8–10: Acceptable for most business writing, trade publications, and general articles.
Score 10–12: Suitable for professional publications and B2B content where readers have domain knowledge.
Score 13–17: Academic or technical. Appropriate for specialists, but risky for mixed audiences.
Score 18+: Very foggy. Most readers will struggle. Time to revise.

The Flesch-Kincaid vs Gunning Fog comparison is one of the most common questions people ask. Both produce grade-level scores, but they often disagree. Gunning Fog tends to produce scores one to two grades higher than Flesch-Kincaid for the same text, because it penalizes polysyllabic words more aggressively. ProWritingAid's own documentation notes this discrepancy and recommends using Gunning Fog specifically for business and journalistic content where complex vocabulary is a real problem.

When I tested a 500-word excerpt from a typical corporate annual report, Flesch-Kincaid came back at grade 11, while Gunning Fog scored 14.2. The Fog score was more useful there, because the issue wasn't sentence length at all. Sentences were actually fairly short. The problem was word choice: "synergistic," "operationalize," "monetization," and similar terms that inflate Fog scores appropriately.

The contrarian take on Gunning Fog: it can overpenalize necessary technical terms. If you're writing for an audience of engineers, words like "infrastructure" or "algorithm" are basic vocabulary, not complexity. The formula doesn't distinguish between words that are complex for your audience and words that happen to have three syllables. Keep that in mind before you start replacing perfectly appropriate terminology just to lower your Fog score.

Coleman-Liau Index and ARI: The Character-Based Readability Formulas

Most readability formulas count syllables. Coleman-Liau and the Automated Readability Index (ARI) count characters instead. That's not just a technical difference. It fundamentally changes what these formulas penalize and makes them particularly useful in digital contexts.

The Coleman-Liau Index uses this formula: 0.0588L - 0.296S - 15.8, where L is the average number of letters per 100 words and S is the average number of sentences per 100 words. The result is a U.S. grade level. Because it's character-based, it was originally designed for optical character recognition systems in the 1970s that could count letters easily but couldn't reliably identify syllable boundaries.

The Automated Readability Index (ARI) uses: 4.71 × (characters per word) + 0.5 × (words per sentence) - 21.43. Again, a U.S. grade level result. ARI tends to produce the highest grade-level estimates of any common formula. Research documented on dev.to shows that ARI regularly scores one to two grades higher than Flesch-Kincaid for the same text, because character count penalizes long words more aggressively than syllable counting does.

Here's a concrete example of why that matters. The word "through" has one syllable, so Flesch-Kincaid treats it as simple. But it has seven characters, so ARI penalizes it more. This is arguably more honest: "through" is an irregular word that non-native English speakers and developing readers genuinely struggle with, even though it's monosyllabic. Coleman-Liau and ARI catch things that syllable-based formulas miss.

When are these formulas more accurate? In digital content environments where text is processed programmatically, character counting is faster and more reliable than syllable parsing. Syllabification rules in English are genuinely complex, and different tools implement them differently, which is one reason the JAMA Network Open study found such wide score variation. Character counting is unambiguous: every tool will count the same number of characters in the same word.

Coleman-Liau vs ARI: they're close cousins, but Coleman-Liau is slightly more lenient. Both are good choices for technical documentation, software UI copy, and digital content that gets processed by automated systems. Neither works well for poetry or heavily hyphenated content, where character counts become misleading.

A common mistake I've seen is using ARI alone for content targeting non-native English speakers. Because ARI produces the highest grade estimates, writers sometimes over-simplify their vocabulary in response, cutting out words that are actually common in their readers' specific vocabulary. Use ARI as an upper-bound check, not as the sole arbiter of complexity.

SMOG Index and Dale-Chall: The Most Conservative Readability Formulas

These two formulas have earned their reputation in high-stakes writing contexts. Healthcare organizations, government agencies, and legal writers lean on SMOG and Dale-Chall because they tend to be more conservative and more accurate for audiences with lower literacy levels. Getting these right isn't just about clarity. In some contexts, it's about patient safety and legal comprehension.

The SMOG Index (Simple Measure of Gobbledygook, a name G. Harry McLaughlin clearly had fun with) works by counting polysyllabic words across exactly 30 sentences: 10 from the beginning, 10 from the middle, and 10 from the end of a document. The formula is: 3 + √(polysyllabic word count). The output is a U.S. grade level representing the education level someone needs to understand the text on first reading.

The SMOG Index is considered the gold standard for health literacy assessment. The American Medical Association and the National Institutes of Health both recommend targeting a SMOG score below 8 for patient-facing materials. Research published in JAMA Network Open in 2023 found that the SHeLL Editor (Sydney Health Literacy Lab) showed the best agreement with manual SMOG calculations, with less than one grade level of variance. Other tools were much less reliable, with some showing variance of several grade levels on the same health document.

What makes SMOG conservative? It measures the grade level required for 100% comprehension, not 50% or 75% comprehension. That's intentional. When you're writing discharge instructions for a hospital patient who may be stressed, medicated, and worried, you need them to understand everything, not most things.

The Dale-Chall Readability Formula takes a completely different approach. Instead of measuring word or sentence length, it compares words against a list of 3,000 words familiar to the average 4th-grade student. Words not on that list are considered "difficult." The formula is: 0.1579 × (difficult words / total words × 100) + 0.0496 × (total words / total sentences), with an adjustment factor added when the percentage of difficult words exceeds 5%.

Dale-Chall is particularly useful for children's educational content and for writing aimed at adults with lower literacy levels. The output maps to grade ranges rather than specific grades, which is slightly awkward but reflects the reality that reading ability isn't a precise scale.

The significant limitation of Dale-Chall is that its word list was created in 1948 and updated in 1995. Modern technology terms, internet vocabulary, and contemporary cultural references don't appear on it. ReadabilityFormulas.com announced updated word lists in 2025 to address this, which is a welcome development, but any tool using the original 1948 or 1995 list will flag "email," "website," and "smartphone" as difficult words, which is clearly wrong for most modern audiences.

My recommendation: use SMOG for any health, safety, legal, or government content. Use Dale-Chall for content aimed at children or adults with limited literacy, but verify your tool is using an updated word list. Both formulas together give you a strong picture of whether your most critical content is genuinely accessible.

Comparison Table: All 7 Readability Formulas at a Glance

Here's a consolidated reference table to make direct comparisons easier. When you're deciding which formula applies to your work, this is the at-a-glance view that cuts through the noise. Note the bias column especially: every formula has a blind spot, and knowing yours helps you interpret scores more accurately.

Formula	What It Measures	Output Scale	Ideal Score (General)	Best Use Cases	Key Limitation / Bias
Flesch Reading Ease	Syllables per word + words per sentence	0–100 (higher = easier)	60–70 for general audiences	Web copy, blogs, consumer content, quick checks	Underpenalizes jargon; short technical sentences score too well
Flesch-Kincaid Grade Level	Syllables per word + words per sentence	U.S. Grade (K–college)	Grade 6–8 for general; 8–10 for professional	Education, marketing, general publishing, Microsoft Word users	Syllable counting varies between tools; misses jargon
Gunning Fog Index	Sentence length + percentage of polysyllabic words	U.S. Grade	8–10 for business; 6–8 for general	Business writing, journalism, corporate communications	Overpenalizes necessary technical terms; no audience adjustment
Coleman-Liau Index	Characters per word + sentences per 100 words	U.S. Grade	Grade 7–9 for general audiences	Digital content, automated systems, programmatic text processing	Penalizes long simple words (e.g., "through"); no syllable nuance
ARI (Automated Readability Index)	Characters per word + words per sentence	U.S. Grade	Grade 6–8 (scores run 1–2 grades high)	Technical writing, software documentation, digital text	Produces highest grade estimates; can trigger over-simplification
SMOG Index	Polysyllabic words across 30 sentences	U.S. Grade	Below grade 8 for health/gov; below 6 for patient materials	Healthcare, safety, legal, government documents	Requires minimum 30 sentences; labor-intensive manual application
Dale-Chall	Percentage of unfamiliar words (vs. 3,000-word list)	Grade range bands	Grade 4–5 range for broad accessibility	Children's content, low-literacy adult audiences, public health	Word list is outdated (1948/1995); flags modern terms as "difficult"

One thing this table makes clear: no single formula covers every situation. The 2023 JAMA study reinforced this by finding that tool-to-tool variance using the same formula could reach 12.9 grade levels on identical text. Standardizing your text preparation (removing mid-sentence periods, handling abbreviations consistently) reduced that to about 2.1 grades in controlled conditions, but even that's a meaningful margin when you're targeting a specific reading level. Running multiple formulas and comparing results gives you a much more honest picture than any single score.

Which Readability Formula Should You Use? A Decision Framework

There's no single right answer to "which readability formula is best," and anyone who tells you otherwise is oversimplifying. The best formula depends on your audience, your content type, and the consequences of getting it wrong. Here's a practical framework to work through.

Start with your audience. Who is actually going to read this content?

If you're writing for patients, caregivers, or the general public on health topics, start with SMOG. Aim below grade 8. The SMOG Index was literally designed for this context, and healthcare literacy organizations use it as the benchmark.
If you're writing for children or adults with limited formal education, use Dale-Chall alongside SMOG. Check that your tool uses an updated word list.
If you're writing for a general consumer audience (web content, e-commerce, news), use Flesch Reading Ease as your primary check. Target 60–70. Add Flesch-Kincaid Grade Level for a grade-level sanity check.
If you're writing for a business or professional audience, Gunning Fog is your friend. It catches the corporate language bloat that Flesch-Kincaid often misses.
If you're writing technical documentation or your text will be processed programmatically, use Coleman-Liau or ARI. Their character-based approach is more consistent across tools.

Consider the stakes. For casual blog posts, one formula is probably fine. For legal disclosures, patient instructions, or anything where comprehension directly affects safety or compliance, run at least three formulas and look for consensus.

The consensus approach is worth taking seriously. Researchers at textlens (dev.to) demonstrated that averaging the grade-level outputs of multiple formulas (excluding Flesch Reading Ease, which uses a different scale) produces a more stable "consensus grade" that reduces the error of any single formula. If your Flesch-Kincaid says grade 9, your SMOG says grade 11, and your Coleman-Liau says grade 10, the average of 10 is probably more trustworthy than any individual score.

Consider your content type:

Blog posts and articles: Flesch Reading Ease + Flesch-Kincaid Grade Level. Target 65+ and grade 8 respectively.
Healthcare and patient content: SMOG primary, Dale-Chall secondary. Target SMOG below 8.
Legal and government documents: SMOG + ARI. Use the higher score as your benchmark.
Business and corporate writing: Gunning Fog. Target below 12 for mixed audiences.
Children's educational content: Dale-Chall + Flesch Reading Ease.
Technical documentation: Coleman-Liau + ARI.
All of the above / unsure: Run all available formulas and look at the consensus.

The most common mistake I see is people picking one formula because it's the default in their tool and then reporting that score as definitive. If you're writing healthcare content and your tool only shows Flesch-Kincaid, you're not getting the information you need. That's not the tool's fault if you know what it does, but it becomes a problem when writers assume Flesch-Kincaid is the complete picture.

Also remember what TeamBench.ai's 2026 research summary put well: no single formula is perfect. Cross-validating across Flesch-Kincaid, Dale-Chall, and SMOG is the professional standard for serious readability work. Use formulas as a diagnostic starting point, then read your own text out loud. If you stumble, your readers probably will too.

How to Check Your Readability Score Using Our Readability Checker

Knowing the theory is useful, but at some point you need to actually run your text through a formula and get a number. Here's a practical walkthrough of how to do that efficiently, and why running multiple formulas simultaneously saves you time and gives you better results.

The Readability Checker at Tools for Writing calculates six readability formulas at once from a single paste of your text. That matters for reasons we've already established: any single formula has blind spots, and seeing all six together immediately tells you whether your scores are clustered (reliable) or spread apart (a signal that something unusual is happening in your text).

Here's how to use it effectively:

Step 1: Prepare your text. Before pasting, remove things that will confuse formula calculations. Take out headers, bullet points, and standalone titles if you want to analyze flowing prose. Make sure your text has enough sentences to be meaningful. SMOG, for example, requires at least 30 sentences to produce a valid score. For very short snippets, treat formula results as rough estimates rather than precise measurements.

Step 2: Paste and run. The checker will return scores across all six formulas simultaneously. Look first at whether the grade-level scores cluster together. If most formulas agree you're around grade 8–10, that's a reliable reading. If one formula says grade 6 and another says grade 14, dig into why. Often it means your text has unusually short sentences paired with unusually complex vocabulary, which different formulas weight differently.

Step 3: Read the sentence highlighting. A good readability tool doesn't just give you a number. It shows you which sentences are flagged as difficult. That's where the real actionable information lives. A sentence-level view tells you exactly where to focus your revisions rather than making blanket changes to your entire document.

Step 4: Compare against your target. Know your target before you start. For general web content, you're aiming for Flesch Reading Ease above 60 and a Flesch-Kincaid grade below 9. For health content, aim for SMOG below 8. Adjust based on the audience framework from the previous section.

You can also use the Word Counter tool to get a quick baseline on your text's structure: total words, sentences, and average sentence length. These numbers feed directly into readability formulas, so understanding them helps you diagnose problems before running the full analysis. If your average sentence length is 28 words, you know immediately that sentence length is a likely source of high difficulty scores, even before you see the formula results.

One practical note: if you're revising content to hit a specific readability target, don't chase the number obsessively. The goal is clearer writing, not a lower score. Splitting a complex sentence mechanically just to reduce word count per sentence can actually make text less coherent. Focus on genuine clarity: shorter sentences where complexity doesn't serve the reader, simpler word choices where a simpler word exists and means the same thing, and active constructions that are easier to parse. The scores should follow naturally from that work.

Frequently Asked Questions

What is Flesch Reading Ease and how is it different from Flesch-Kincaid Grade Level?

Flesch Reading Ease produces a score from 0 to 100, where higher scores mean easier text. A score of 60–70 is considered standard for general audiences like newspapers. Flesch-Kincaid Grade Level uses the same inputs (syllables and sentence length) but converts them to a U.S. school grade equivalent. A grade of 8 means an 8th grader should be able to read the text. They're related formulas, but the output scales are completely different, so you can't compare a Reading Ease score of 65 to a Grade Level score of 8 directly.

Flesch-Kincaid vs Gunning Fog: which one should I use for business writing?

For business writing, Gunning Fog is generally more useful. It specifically targets polysyllabic words, which are the main culprit in corporate writing bloat. Flesch-Kincaid focuses more on sentence length, which is less of a problem in business documents where sentences are often short but vocabulary is dense. Gunning Fog typically produces scores one to two grades higher than Flesch-Kincaid on the same text, which often reflects a more accurate picture of how difficult business prose actually is to read.

What does a readability score mean in practical terms?

A grade-level readability score represents the U.S. education level someone needs to comfortably understand your text. A score of 8 means 8th grade reading ability. The important context is that the average American adult reads comfortably at a 7th to 8th grade level, according to the National Assessment of Adult Literacy. So writing at grade 8 is not dumbing down your content. It's writing for your actual audience. For specialized professional audiences, grades 10–12 may be appropriate, but anything consistently above 12 warrants a review.

SMOG index explained: why do healthcare writers prefer it?

SMOG (Simple Measure of Gobbledygook) estimates the education level required for 100% comprehension, not partial understanding. That's different from most other formulas, which target some lower comprehension threshold. For healthcare and safety writing, you need readers to understand everything, not most things. Both the American Medical Association and National Institutes of Health recommend targeting a SMOG score below 8 for patient-facing documents. It requires at least 30 sentences to calculate accurately, but that requirement also forces writers to work with documents of meaningful length.

Which readability formula is best overall?

No single formula is universally best, and anyone recommending one without knowing your audience and content type is guessing. The professional approach is to run multiple formulas and look for consensus. For general content, Flesch Reading Ease plus Flesch-Kincaid works well. For health and government content, add SMOG. For technical writing, add Coleman-Liau or ARI. When formulas disagree significantly, investigate why rather than just picking the most favorable score.

Why do different readability calculators give different scores for the same text?

A 2023 study in JAMA Network Open found that the same text could produce scores varying by up to 12.9 grade levels across eight different tools using the same formula. The main causes are different rules for handling punctuation, abbreviations, contractions, and sentence boundaries. Some tools also implement syllable-counting differently. To reduce this variance, standardize your text before analysis: remove headers and list items that aren't full sentences, expand abbreviations, and make sure your text is clean flowing prose. This preparation can reduce the inter-tool variance from 12.9 grades to around 2.1 grades.

Can readability formulas work for languages other than English?

Most standard formulas (Flesch, SMOG, Gunning Fog, Coleman-Liau) were developed specifically for English and don't transfer well to other languages. The Lix formula is the main exception, having been designed with multilingual use in mind, with a target score below 40 for general audiences. If you need readability analysis for non-English content, look specifically for tools that support your target language or use Lix as a language-agnostic approximation.

How accurate are readability formulas at predicting actual comprehension?

Research shows correlations of approximately 0.7 between formula scores and tested comprehension. That's a meaningful relationship, but it's not deterministic. Readability formulas measure surface features of text: word length, sentence length, syllable counts. They cannot measure logical coherence, whether an analogy is accurate, whether the reader is motivated to engage, or whether the vocabulary is familiar to a specific audience even if it's technically "complex." Use formula scores as a useful signal and diagnostic tool, but pair them with actual reader testing whenever the stakes are high.