Ecologic niche modeling has allowed numerous advances in understanding the geographic ecology of species, including distributionalpredictions, distributionalchange and invasion, and assessment of ecologic differences. We used this toolto characterize ecologic differentiation of Triatoma brasiliensis populations, the most important Chagas’ disease vector in northeastern Brazil. The species’ ecologic niche was modeled based on data from the Fundação Nacionalde Saúde of Brazil(1997–1999) with the Genetic Algorithm for Rule-Set Prediction (GARP). This method involves a machine-learning approach to detecting associations between occurrence points and ecologic characteristics of regions. Four independent “ecologic niche models” were developed and used to test for ecologic differences among T. brasiliensis populations. These models confirmed four ecologically distinct and differentiated populations, and allowed characterization of dimensions of niche differentiation. Patterns of ecologic similarity matched patterns of molecular differentiation, suggesting that T. brasiliensis is a complex of distinct populations at various points in the process of speciation.