The effectiveness of a geology-slope logistic regression (logit) model versus a borehole-slope logit model was compared and evaluated to determine the most suitable method for use in creating landslide susceptibility maps in a 15.54-km2 (6-mi2) area southwest of Colorado Springs. The inputs of the geology-slope logit model include readily available geology and topography data. The borehole-slope logit model uses data collected in the field and produced through laboratory experiments; these inputs include unit weight, cohesion, friction angle, and groundwater depths in addition to topography data. The results of both models were compared and evaluated for their accuracy using the area under the receiver operating characteristics (ROC) curve method. Landslide susceptibility maps were created specifically to failure mechanisms present in the study area, including circular failures within the colluvium deposits, circular failures within the weathered shale, and planar failures within the weathered shale. The results show that the geology-slope model yields an area under the ROC curve ranging from 53 percent to 62 percent. The area under the ROC curve for the borehole-slope model ranges from 52 percent to 79 percent. The borehole-slope model outperformed the geology-slope model for circular failures in the colluvium deposits and planar failures within the weathered shale, while the geology-slope model slightly outperformed the borehole-slope model for circular failures within the weathered shale. This study provides insight into the effectiveness of using existing geology and topography data for a rapid assessment of landslide susceptibility.