Willits, CA
How exposed is Willits to wildfire?
Out of every US place USFS scores, Willits lands at the 89th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 2,420 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Willits at the 88th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
2,420 buildings are counted in Willits, and 79.4% of them are Indirect exposure — ember-driven risk rather than the 20.6% in Direct exposure or the 0% rated Minimal.
Where Willits ranks
Willits's 89th national percentile looks worse in isolation than its 60th ranking inside California does — this place is on the milder end for its own state, by 30 points. Among the 31,521 US communities USFS scores, Willits ranks 3,333 for wildfire risk (1 is highest) and 6,464 by building count (1 is largest). Within California alone, it ranks 632 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
What this risk score means for insurance
Willits's 89th-percentile score lands in California, the only two states requiring a wildfire disclosure at sale. California's surplus-lines homeowners market passed 300,000 policies for the first time in 2025, driven by carriers pulling back from wildfire-exposed areas statewide. The disclosure-law guide covers what it requires.
Hardening a home in Willits
Because 79.4% of Willits's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Willits's figures come from
Willits's 89th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Willits's dominant indirect exposure actually means, with real examples from across the dataset.