India ranks as the second most landslide-prone country globally. The tectonically active and geomorphologically diverse Western Himalaya, particularly the Jammu and Kashmir region, is highly susceptible to landslides due to natural and anthropogenic factors. This study focuses on its ten districts, with six of them being considered as India’s most landslide-vulnerable areas. An integrated geomorphological, geological, and geotechnical approach is employed to assess the landslide dynamics in these districts. Twenty important causal factors derived from field-based geospatial and secondary data were taken into consideration, which was later classified into geological, geomorphological, hydrological, and environmental categories. A comprehensive landslide inventory is compiled using the data from authoritative sources. Spatial analysis was performed under the ArcGIS and MATLAB platforms, and the frequency ratio model was applied for unbiased landslide susceptibility assessment. The results produced a susceptibility map that identified three zones: high, moderate, and low risk. Critical hotspots include northern Anantnag, northeastern Riasi and Ramban, and southeastern Udampur. Probabilistic likelihood ratios distinguished positive and negative sub-factor correlations, while spatial multi-criteria evaluation, normalized and integrated into an adaptive neuro-fuzzy inference system, refined vulnerability classification. The findings categorized the region into three distinct risk levels: all ten districts showed moderate susceptibility, eight districts out of ten exhibited moderate to high vulnerability, and four were classified as having moderate to low risk. This study provides critical insights for landslide hazard zonation in the Western Himalaya, emphasizing data-driven zonation for further decision-making.