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Lyme disease and tick-borne encephalitis were recognized recently in the Province of Trento, Italian Alps. Assessment of areas of potential risk for these tick-borne diseases is carried out by a model based on classification and regression trees (CART), using both discrete and continuous variables. Data on Ixodes ricinus (L.) occurrence resulted from extensive sampling carried out by standard methods in 99 sites over an area of approximately 2,700 km2 in the Province of Trento. A series of environmental parameters were recorded from each site and population densities of roe deer, Capreolus capreolus (L.), were considered. The CART model discriminates 2 variables that appear to have the greatest effect on the mesoscale occurrence of ticks: altitude and geological substratum, with a drastic decrease of tick frequency above an altitude of approximately 1,100 m and on volcanic substrata. The model is effective in identifying the mesoscale areas at greater potential risk, with a relatively low sampling effort.