The state of Meghalaya of the North Eastern Region (NER) of India, situated in the India Himalayan Region (IHR), is the rainiest place in the country and falls under seismic zone V. The Himalayan ranges account for 80% of total landslide hazards in India. The main goal of the present study is to generate the GIS-based landslide susceptibility map (LSM) of Meghalaya by using frequency ratio (FR), Shannon entropy (SE), analytical hierarchy process (AHP), and fuzzy-AHP (FAHP) models and compare these models for the study area. Fifteen landslide conditioning factors are used for susceptibility mapping includes a slope, aspect, elevation, plan curvature, stream power index (SPI), topographic wetness index (TWI), land use land cover (LULC), normalized difference vegetation index (NDVI), distance from the river, road and faults, rainfall (30 years mean annual rainfall), soil texture, geomorphology, and lithology. Landslide inventory of 1330 landslide events is prepared and mapped from various sources. The inventory dataset is randomly split in a 70/30 ratio to make the training dataset (70%) used in the model and testing dataset (remaining 30%) for validation purposes. The southern escarpment, the southeast region of the study area, and hillslope along the roadside show high susceptibility for landslide occurrence in all four models. The LSMs produced in the present study are validated using the area under curve (AUC) value. The presented LSMs can help concerned authorities and planners to make sustainable development plans and formulate risk mitigation strategies keeping in mind the critical areas for landslide hazards.