Bokchito, OK
Bokchito wildfire risk explained
Out of every US place USFS scores, Bokchito lands at the 84th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 445 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Bokchito's burn probability — fire likelihood with no building count factored in — sits at the 86th percentile nationally.
Bokchito's building exposure, zone by zone
Indirect exposure is dominant in Bokchito (69.7% of 445 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 30.3% sit in the Direct zone.
Bokchito against the rest of the country
Bokchito's 84th national percentile looks worse in isolation than its 30th ranking inside Oklahoma does — this place is on the milder end for its own state, by 54 points. Among the 31,521 US communities USFS scores, Bokchito ranks 4,956 for wildfire risk (1 is highest) and 18,367 by building count (1 is largest). Within Oklahoma alone, it ranks 582 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Shopping for coverage in Bokchito
Bokchito's 84th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Because 69.7% of Bokchito'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 Bokchito's figures come from
Bokchito's 84th-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 Bokchito's dominant indirect exposure actually means, with real examples from across the dataset.