Crest, CA
Crest wildfire risk explained
Crest's 1,453 buildings earn a 98th-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.)
Fire likelihood alone (USFS's burn-probability figure) ranks Crest at the 98th national percentile — 0 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Crest's buildings actually sit
Of Crest's 1,453 counted buildings, 62.8% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
How Crest compares
Crest's risk sits at a similar level relative to California (84th percentile statewide) as it does nationally (98th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Crest ranks 592 for wildfire risk (1 is highest) and 9,380 by building count (1 is largest). Within California alone, it ranks 249 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
Crest sits in California, one of two states that legally require a wildfire-risk disclosure at sale. California's FAIR Plan, the state's insurer of last resort, ended 2025 with 668,609 residential policies after adding 21,859 in Q4 alone — the kind of market shift a 98th-percentile score like Crest's can end up mattering for. More on the disclosure law.
What would actually reduce this score
Crest's 62.8% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Crest's figures come from
Crest's 98th-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 Crest's dominant direct exposure actually means, with real examples from across the dataset.