Landslide susceptibility assessment is a primary tool for understanding the basic characteristics of slopes that are prone to landslides. In this study, a landslide susceptibility assessment was accomplished, by adopting the Statistical Index Method (SIM) and the Analytic Hierarchy Process (AHP). Ten landslide causing factors were considered including: elevation, slope, aspect, lithology, land use, drainage density, plan curvature, precipitation, geomorphologic faces, and rock unit’s sensitivity to erosion. The SIM was used to determine the weighted value (Si) for classes of every landslide causing factor, the AHP was utilized to determine the weighted value (Wi) for every factor. The summation of the product of Si by Wi represent the landslide Susceptibility Index (LSI) value for every pixels. Based on the derived LSI, landslide susceptibility map (LSM) was produced then the study area was grouped into five susceptibility classes. The densities of landslide for five susceptibility classes implying there is a satisfactory agreement between the susceptibility map and the actual landslide data. In the following, the results of the LSM were quantitatively validated using observed landslide dataset and the receiver operating characteristic (ROC) method. The validation results showed that the AUC for prediction rate of model was 95.2%. The landslide susceptibility showed the areas with lithology of old terraces, young terraces, lahar, and porphyritic trachyandesite-trachyte with different degrees of sensitivity to erosion which distribute between 10–40% slope and more than 60% are very prone to slope failure. Therefore, SIM and AHP were found to be effective models for landslide susceptibility mapping.