Nepal is susceptible to multiple disasters, with landslides being one of the most prominent. This study was conducted to assess landslide susceptibility in Palungtar Municipality, Gorkha by employing multiple modeling approach. The model adopted in this study include Bivariate Statistical: Information Value (IV) and Multi Criteria Decision Analysis (MCDA): Heuristic and Analytical Hierarchical Process (AHP). The Heuristic and AHP models are based on the opinion of researchers and experts whereas Information value (IV) relies on the empirical data and interpretation. The models incorporated eleven causative parameters responsible for instability in the area namely Slope, Aspect, Land Use Land Cover (LULC), Plan Curvature, Profile Curvature, Distance from River, Distance from Road, Normalized Difference Vegetation Index (NDVI), Normal- ized Difference Water Index (NDWI), Topographic Wetness Index (TWI), and Geology. The models were trained and tested (validated) using 70 (Seventy) landslide patches identified through ground-truthed Google Earth imagery. Heuristic and AHP models designated 13.13 and 11.42% of the total study area as highly susceptible, respectively, while the Information Value (IV) model identified 10.38% for the same classification. Area under the Receiver Operator Characteristic Curve (AUC), an analytical tool, was utilized to validate the model prediction. The AUC values for Heuristic, AHP and Information Value (IV) models was found to be 0.825, 0.846 and 0.927, respectively. It can be concluded that although all models demonstrate substantial prediction capability, Information Value (IV) model exhibits comparatively higher prediction accuracy.