ToolNestFlesch-Kincaid vs Gunning Fog
Flesch-Kincaid gives you a US school grade level; Gunning Fog estimates years of formal education needed — both from sentence length, but they count 'hard words' differently. Compare both on your text with our free readability score calculator; the formulas and verdict are below.
The two formulas, side by side
The Flesch-Kincaid Grade Level formula is: 0.39 × (words ÷ sentences) + 11.8 × (syllables ÷ words) − 15.59. The result maps directly to a US school grade: 8.0 means an eighth-grader should understand it. Developed by J. Peter Kincaid for the US Navy in 1975, it recalibrated Rudolf Flesch's 0–100 ease scale into grade levels the military could write into training-manual contracts. The Gunning Fog Index, created by Robert Gunning in 1952 for newspaper writing, is: 0.4 × ((words ÷ sentences) + 100 × (complex words ÷ words)), where 'complex words' are words of 3+ syllables, excluding proper nouns, familiar jargon, and compound words. The result estimates years of schooling needed: 12 is a high-school senior, 16 a college graduate, 17+ a graduate degree. The structural difference matters: Flesch-Kincaid weights average syllables per word (continuous), while Fog counts the percentage of long words (a threshold). A text with many 2-syllable words and a few 5-syllable monsters scores moderately on Flesch-Kincaid but high on Fog, because Fog's 3-syllable cutoff treats 'television' and 'antidisestablishmentarianism' identically. Both formulas share the sentence-length term, so shortening sentences helps both scores equally — the divergence is entirely in how they price vocabulary.
Worked example: the same text, both formulas
Test paragraph: 180 words, 12 sentences, 288 syllables, 36 complex words (3+ syllables). Flesch-Kincaid: ASL = 180 ÷ 12 = 15.0; ASW = 288 ÷ 180 = 1.60. Grade = (0.39 × 15.0) + (11.8 × 1.60) − 15.59 = 5.85 + 18.88 − 15.59 = 9.14 — ninth grade. Gunning Fog: complex-word percentage = 100 × 36 ÷ 180 = 20%; Fog = 0.4 × (15.0 + 20) = 14.0 — fourteen years of education, roughly a college sophomore. Same text, five levels apart — which is normal and expected, not a contradiction. The gap comes from the 36 complex words: they are 20% of the vocabulary, and Fog punishes that concentration while Flesch-Kincaid averages it out. Now simplify the vocabulary — replace the 36 complex words with plainer terms, dropping syllables to 234 and complex words to 9: Flesch-Kincaid becomes (0.39 × 15) + (11.8 × 1.30) − 15.59 = 5.85 + 15.34 − 15.59 = 5.60; Fog becomes 0.4 × (15 + 5) = 8.0. Both fell, but Fog fell 6 points versus Flesch-Kincaid's 3.5 — Fog is the more vocabulary-sensitive metric, which is exactly why editors use it to hunt jargon. Run your own draft through a readability calculator that reports both, and the gap between them tells you whether your problem is sentences (both high) or vocabulary (Fog much higher).
When to use each one
Use Flesch-Kincaid when the audience is defined by school grade: K-12 educational materials, children's books, government plain-language compliance (many US agencies target grade 8–10), and any contract that specifies a grade level. Its output is intuitive to non-specialists — 'grade 9' needs no explanation — and Microsoft Word's built-in readability statistics report it, so it is the formula most writers have already seen. Use Gunning Fog when the audience is adult professionals and the risk is jargon density: business reports, journalism, marketing copy, and technical writing for non-specialists. Fog's complex-word percentage maps directly onto an editing action — find the 3+ syllable words and cut their share — which makes it the better revision tool even when you report Flesch-Kincaid. The newspaper industry's rule of thumb: keep Fog under 12 for general audiences, under 10 for mass-market. Neither formula suits highly technical or legal writing, where the terminology is the content — both will flag a cardiology paper as 'needs graduate school,' which is true and unhelpful. For multilingual or ESL audiences, prefer Flesch Reading Ease bands over either grade metric, since US grade levels do not transfer. Practical workflow: draft to a Flesch-Kincaid target for compliance, then revise against Fog to kill jargon — the two metrics in sequence do what neither does alone. Our grade-level estimation guide walks through the manual calculation when you want to verify a tool's math by hand.
What the formulas miss (and what to do about it)
Both formulas share the same blind spots, because both reduce reading to two surface features. They ignore structure: a Fog-8 wall of text with no headings is harder to use than a Fog-12 article with clear sections, summaries, and bullet points. They ignore cohesion: 'The cat sat. The mat was red. It rained.' scores beautifully and reads terribly — short sentences with no logical connection are the easiest way to game both metrics. They ignore reader knowledge: 'photosynthesis' is a complex word to a second-grader and a simple word to a botanist; Fog counts it the same either way. They miscount systematically: proper nouns, abbreviations, and hyphenated compounds inflate complex-word counts, so a paragraph about 'Worcestershire' or 'e-commerce' scores harder than it reads. The professional response is triangulation: use the grade metrics for calibration, then check structure (paragraphs under ~120 words, descriptive headings every 200–300 words), cohesion (read transitions aloud), and audience fit (would my reader know this term?). The formulas are excellent at catching drift — a section that scores 6 grades harder than the rest of the document has a real problem — and weak at judging absolute quality. Treat a stable, in-band score as a green light to stop editing the surface and start editing the ideas. For the companion length metrics, see our word counter and the guide to counting words. Developers embedding these checks in a docs pipeline can convert markdown sources with our markdown to HTML converter before scoring.