Orosi, CA
Orosi, CA's wildfire risk, in USFS's own numbers
Orosi's 2,201 buildings earn a 84th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Orosi at the 85th percentile, close to its 84th-percentile risk score.
Where Orosi's buildings actually sit
Only 18% of Orosi's 2,201 buildings carry Direct exposure and 0% carry Indirect; the remaining 82.1% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Where Orosi ranks
Inside California, Orosi sits at just the 46th percentile even though it scores 84th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Orosi ranks 5,195 for wildfire risk (1 is highest) and 6,932 by building count (1 is largest). Within California alone, it ranks 848 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
Orosi's 84th-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.
Lowering exposure, not just insuring around it
Orosi's 82.1% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Orosi's figures come from
Every one of the two percentiles behind Orosi's 5,195-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Orosi's dominant minimal exposure actually means, with real examples from across the dataset.