Climate change and flooding are related issues on the Earth's surface, while numerous lowland areas, especially delta regions, are mostly affected by flood hazards. Hence, flood susceptibility mapping and the simulation of future effect areas are essential for hazard management and awareness. The river floodplain areas of the Ganga River in the Bihar state are the most affected due to high annual floods. Floods cause huge economic losses and environmental degradation, such as deforestation, riverbank erosion, and water quality loss. Thus, flood vulnerability measurement is a serious concern in this area, which involves building proper awareness and mitigation strategies to achieve sustainable development goals. Remote Sensing (RS) is widely applied to such hydrological issues. Hence, statistical approaches, such as the Analytical Hierarchy Process (AHP), Frequency Ratio (FR), and Fuzzy-AHP (FAHP) algorithms, were applied for flood susceptibility analysis in the selected flood plain of the Ganga River in the Bihar state. The most suitable flood susceptibility areas of three different approaches were 9604.21 km2 (AHP), 9712.48 km2 (FAHP) and 9598.28 km2 (FR), while river and channel areas were selected as not suitable area. The flooded maps indicated the flooded lands using Google Earth Engine (GEE) of different years are 2977.69 km2 (2020), 10481.63 km2 (2021), and 1103.89 km2 (2022), respectively. The results of the current study indicate that this area is essentially in need of serious attention for future hazard management and adaptation strategies for the reduction of flooded areas, in addition to the reduction of socio-economic variability in monsoon regions. Otherwise, floods destroyed cropland, increased food scarcity, and caused huge socio-economic losses.