In this study, predictive models of geographic distribution patterns of Triatoma pseudomaculata (Tps) and T. wygodzinskyi (Twy) were carried out. They were based on biophysical variables estimated from information provided by the satellite remote sensors AVHRR (Advanced Very High Resolution Radiometer) and MODIS (MODerate-resolution Imaging Spectroradiometer). Our goal was to analyze the potential geographic distribution of Tps and Twy and to assess the performance of three predictive models (one for each species and one for both species together) based on temperature, vapour pressure deficit, vegetation and altitude. The geographic distribution analysis shows that all models performed well (>85.7% of overall correct classification of presence and absence point data). The MODIS-based models showed lower correct classifications than the AVHRR-based models. The results strongly suggest that environmental information provided by remote sensors can be successfully used in studies on the geographic distribution of poorly understood Chagas disease vector species.