How the Flesch-Kincaid and Gunning Fog Formulas Actually Measure Reading Difficulty

In 1952, an American business consultant named Robert Gunning published The Technique of Clear Writing, arguing that "unclear writing was not a sign of sophistication but of muddled thinking." He observed that the fog of unnecessarily complex prose was costing corporations real money in wasted time, and he built a mathematical tool to prove it. Decades later, the US Navy commissioned a similar tool from researchers J. Peter Kincaid and Rudolf Flesch to evaluate technical manuals.[1]

Today, those two algorithms—the Gunning Fog Index and the Flesch-Kincaid Grade Level—are built into nearly every word processor, SEO plugin, and corporate style guide. They dictate how healthcare pamphlets are written, how government forms are drafted, and how digital content is ranked.[1]

Yet neither formula actually reads or understands text. They do not measure clarity, accuracy, persuasiveness, or narrative flow. Instead, they measure the cognitive load of decoding: how much working memory an average reader needs to hold a sentence together while figuring out what each word means.

The insight that powers both formulas is identical. Longer sentences overflow working memory, and longer words activate fewer prior associations, making them harder to decode. By combining those two signals and calibrating them against a corpus of text independently rated for difficulty, the formulas produce a US grade level. A score of 8.0 means an eighth-grader should be able to follow it on the first read.[1]

The Flesch-Kincaid Grade Level is the most widely cited metric, largely because Microsoft integrated it into Word decades ago. It calculates the average number of words per sentence and the average number of syllables per word. The formula multiplies the sentence length by 0.39, multiplies the syllable average by 11.8, and subtracts a constant of 15.59.

Because Flesch-Kincaid averages every syllable across the entire text, it treats a paragraph of mostly two-syllable words exactly the same as a paragraph mixing one-syllable words with a few massive technical terms. The difficulty is smoothed out over the whole sample.

Gunning Fog takes a much sharper approach. Instead of averaging all syllables, it specifically targets "complex words"—defined strictly as words with three or more syllables. The formula adds the average sentence length to the percentage of complex words, then multiplies the total by 0.4.

This structural difference creates massive divergences in how the two formulas score the same text. If a writer replaces a single one-syllable word with a three-syllable word in a standard 100-word passage, Flesch-Kincaid's syllable average barely moves, raising the final score by just 0.236 grade levels.[2]

Under Gunning Fog, that same substitution increases the percentage of complex words by a full point. Multiplied by the 0.4 coefficient, the text jumps by 0.40 grade levels. Mathematically, Gunning Fog penalizes a multisyllabic word 1.69 times harder than Flesch-Kincaid does.[2]

This aggressive penalty makes Gunning Fog highly sensitive to jargon, which is exactly what Robert Gunning intended when evaluating business writing. However, it also creates significant blind spots. The formula cannot distinguish between a genuinely obscure technical term and a common multisyllabic word. "Information," "understanding," and "government" all trigger the complex-word penalty, artificially inflating the grade level of perfectly accessible text.

Flesch-Kincaid has its own blind spots. Because it relies purely on syllable counts, it treats short, rare words as easy and long, familiar words as hard. The word "quip" (one syllable) is scored as simpler than "banana" (three syllables), even though the latter is understood by toddlers.

Relying on a single readability score often leads writers astray. When a corporate policy dictates an 8th-grade reading level, writers frequently dumb down the text by swapping precise technical terms for vague, shorter synonyms, or by chopping flowing sentences into staccato fragments. The score improves, but the actual clarity of the document degrades. A text with high readability should be "accessible to a broader audience—it's clear, concise, and understandable," not just mathematically simple.[1]

The most defensible readability assessment uses several formulas together. If Flesch-Kincaid, Gunning Fog, and character-based formulas like the Automated Readability Index all place a text in the same grade band, the score is highly reliable.

When the formulas disagree, the divergence itself is the diagnostic tool. If Gunning Fog runs three grade levels higher than Flesch-Kincaid, the text is likely dense with specific three-syllable nouns. If character-based formulas spike while syllable-based formulas remain low, the text likely contains unusual spellings or acronyms that confuse the syllable counters.

Readability formulas remain diagnostic instruments, not writing instructors. They can flag when a sentence has grown too unwieldy or when vocabulary has become too dense, but they cannot tell a writer how to fix it. The goal is to reduce the friction of reading, not just to satisfy an algorithm.[2]