The purpose of this study is to assess the susceptibility of landslides in Wen County, China, using both analytical hierarchy process (AHP) and frequency ratio (FR) models. For this, a total of 529 landslides were identified and randomly split into two groups. The modeling group, which represented approximately 70% of the total landslides, was used as a training set to construct the susceptibility maps. The remaining 30% were used for validation purpose. Eight layers of landslide-related factors were prepared, including slope angle, altitude, distance to rivers, distance to roads, distance to faults, rainfall, lithology, and normalized difference vegetation index. Subsequently, landslide susceptibility maps were produced using the models. For verification, an area under curvature (AUC) and the seed cell area index (SCAI) assessments were applied. The AUC plot estimation results showed that the success rates of the AHP and FR models were 83.55 and 88.42% and the prediction rates were 83.43 and 86.62%, respectively. According to the validation results of the AUC and SCAI evaluations, the map obtained from the FR model is more accurate than that from the AHP model. These landslide susceptibility maps can be used for optimum management by decision makers and land-use planners.