Rainfall and earthquake are one of the most important triggering factors for landslides in the Himalayan hilly terrain. Rainfall following an earthquake or vice versa can have cumulative effects on slope stability. Considering the possibility of simultaneous or cascading hazards is pivotal for a comprehensive understanding of the overall hazard in a given area. This study endeavors to conduct a scenario-based analysis to understand the potential impact of simultaneous or sequential multi-triggering landslide hazard assessment for Bhagirathi valley of Indian Himalaya, leveraging machine learning and GIS techniques. Utilizing the remote sensing data, seismic activities, rainfall patterns and topographic data in modeling framework, the study predicts the impact of landslides events in the Bhagirathi valley region prone to both rainfall and earthquake-induced landslides. The topographic maps were prepared using the remote sensing data. The seismic and rainfall maps were prepared to generate the rainfall induced landslide susceptibility map and earthquake induced landslide susceptibility map. By considering both triggering mechanisms, the study provides a more comprehensive perspective on multi-triggering landslide susceptibility scenarios. This information is critical for developing effective risk management strategies and improving the resilience of communities in the region.