Black-tailed prairie dog (BTPD) (Cynomys ludovicianus) populations in Kansas have declined significantly due to both natural and human-induced threats. To minimize the risk of future population declines, it is necessary to identify existing BTPD habitats in the state as well as areas suitable for BTPD habitat. This paper presents a method for modeling BTPD habitats in Kansas using geographic information systems (GIS), remote sensing, and ecological niche modeling with the Genetic Algorithm for Rule-Set Prediction (GARP). Environmental variables incorporated into the ecological niche modeling process include composite biweekly Normalized Difference Vegetation Index (NDVI) layers derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery, slope, soil depth, and soil texture. Species occurrence training and validation data were selected from an aerial survey of BTPD colonies by the Kansas Department of Wildlife and Parks (KDWP). Accuracy assessment methods, including Receiver Operating Characteristic (ROC) analysis, omission calculation, and validation with an independent BTPD colony dataset collected for the Cimarron National Grassland in Morton County, indicate a high degree of accuracy for the GARP models. A map of BTPD habitat suitability produced by the ecological niche modeling has the potential to aid state agencies and organizations in their efforts to prevent further population declines in the species.