Area of habitat (AOH) is a deductive model which maps the distribution of suitable habitats at suitable altitudes for a species inside its broad geographical range. The AOH maps have been validated using presence-only data for small subsets of species for different taxonomic groups, but no standard validation method exists when absence data are not available. We develop a novel two-step validation protocol for AOH which includes first a model-based evaluation of model prevalence (i.e, the proportion of suitable habitat within a species' range), and second a validation using species point localities (presence-only) data. We applied the protocol to AOH maps of terrestrial birds and mammals. In the first step we built logistic regression models to predict expected model prevalence (the proportion of the range retained as AOH) as a function of each species' elevation range, mid-point of elevation range, number of habitats, realm and, for birds, seasonality. AOH maps with large differences between observed and predicted model prevalence were identified as outliers and used to identify a number of sources of systematic error which were then corrected when possible. For the corrected AOH, only 1.7 % of AOH maps for birds and 2.3 % of AOH maps for mammals were flagged as outliers in terms of the difference between their observed and predicted model prevalence. In the second step we calculated point prevalence, the proportion of point localities of a species falling in pixels coded as suitable in the AOH map. We used 48 336 141​​​​​​​ point localities for 4889 bird species and 107 061 point localities for 420 mammals. Where point prevalence exceeded model prevalence, the AOH was a better reflection of species' distribution than random selection. We also found that 4689 out of 4889 (95.9 %) AOH maps for birds, and 399 out of 420 (95.0 %) AOH maps for mammals were better than random. Possible reasons for the poor performance of a small proportion of AOH maps are discussed.