The process of riverbank erosion (RE) is often accelerated by natural events and anthropogenic activities leading to the transformation of this natural process to natural hazard. The present study aims to estimate bank erosion rate and prediction of the lower Ganga River in India using digital shoreline analysis system (DSAS) model. The prediction of RE susceptibility mapping has been generated using three ensemble models such as DSAS, bank erosion hazard index (BEHI), and river embankment breaching vulnerability index (REBVI). For the study satellite images and field data (bank materials, geotechnical parameters, embankment structure, hydraulic pressure etc.) have been used to recognize the river bank position and BEHI and REBVI scores. During 1973-2020, the average bank erosion and accretion rate was found 0.059 km/y and 0.022 km/y at the left bank while 0.026 km/y and 0.046 at the right bank respectively. The prediction results illustrated that the very high vulnerable condition of 06 villages and 21 villages for high vulnerable due to left bank erosion. BEHI and REBVI scores have been the significant performance of understanding and identification of RE vulnerable areas. The long-term (2020-2045) average erosion and deposition rate was predicted at 0.135 km/y and 0.024 km/y at the left bank and 0.043 km/y and 0.045 km/y at the right bank respectively. The prediction accuracy and validation of models were measures by statistical techniques such as student’s t-test, RMSE, and R2 values. This study would be help planners and decision makers the spatial guidelines to understanding future trends of bank erosion and shifting rate for land-use planning and management strategies to protect riverbank.