Identification of landslide potential areas is a prerequisite step for landslide risk reduction. Geo-statistical modeling in terms of landslide susceptibility zonation (LSZ) considering the past landslides and their responsible factors provides a reliable source of information to minimize landslide induced damages. For the present study, 15 factors related to topographical, geological, hydrological, landuse are used to forecast the future landslide locations in and around the Kalimpong region of Indian Himalayas. Two well-known models, namely Fuzzy Analytic Hierarchy Process (FAHP) and Yule coefficient (YC) are adopted to establish the LSZ mapping. These models are not extensively explored in Indian Himalayas, and thus, provide an opportunity to test them in the present study area. Here, FAHP is used to define the relative weights of different factors and YC is used to estimate the subclass weights of each factor. Thereafter, using arithmetic overlay in GIS, landslide susceptibility index (LSI) was obtained. Using this LSI range, class boundaries between five susceptibility zones have been defined by adopting the success rate curve (SRC) technique. Finally, the model performance is gauged through the Area Under Curve (AUC) of the Receiver Operating Characteristic (ROC) curve which shows a prediction accuracy of 85.26%. The findings of this study may helpful in developmental planning and for prescribing integrated landslide preventive measures.