Prado Verde, TX
Prado Verde wildfire risk explained
USFS's Wildfire Risk to Communities model puts Prado Verde at the 12th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 144 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Prado Verde at the 9th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Prado Verde's building exposure, zone by zone
Prado Verde rates 64.6% Minimal exposure against just 35.4% Direct and 0% Indirect — of 144 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Where Prado Verde ranks
There's little gap between Prado Verde's 12th national percentile and its 1st percentile inside Texas, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Prado Verde ranks 27,813 for wildfire risk (1 is highest) and 27,135 by building count (1 is largest). Within Texas alone, it ranks 1,786 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
Shopping for coverage in Prado Verde
Prado Verde's low rating (12th percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Prado Verde
Even with 64.6% of Prado Verde outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Prado Verde's figures come from
Every one of the two percentiles behind Prado Verde's 27,813-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Prado Verde's dominant minimal exposure actually means, with real examples from across the dataset.