Keddie, CA
Keddie wildfire risk explained
Keddie sits at the 99th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 43 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Keddie's burn probability — fire likelihood with no building count factored in — sits at the 99th percentile nationally.
Where Keddie's buildings actually sit
43 buildings are counted in Keddie, and 100% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Keddie against the rest of the country
Keddie's risk sits at a similar level relative to California (92nd percentile statewide) as it does nationally (99th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Keddie ranks 215 for wildfire risk (1 is highest) and 31,095 by building count (1 is largest). Within California alone, it ranks 123 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
Keddie 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 99th-percentile score like Keddie's can end up mattering for. More on the disclosure law.
What would actually reduce this score
Because Direct exposure dominates in Keddie (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Keddie's figures come from
The methodology guide shows exactly how USFS turned 43 counted buildings into the percentiles shown above for Keddie. The exposure-zones guide covers what Keddie's dominant direct exposure actually means, with real examples from across the dataset.