One of the most frequent and destructive natural disasters that threatens infrastructure and human life globally is flood. The complimentary impacts of GIS and multi-criteria decision making (MCDM) enhance the efficacy and results of flood analysis. Ten thematic layers, including slope, elevation, geomorphology, rainfall, Topographic Wetness Index (TWI), land use land cover (LULC), flow accumulation, population density, drainage density, and number of households, were developed for study area to determine a suitable location. All the maps were generated and standardized by reclassifying each thematic map into five classes which were further used as input for both MCDM methods. Each parameter had been assigned the weightage on a scale of one to nine based on importance to a potential flood zonation. Based upon AHP and TOPSIS approximately 5% of the total region falls under very high flood hazard zones. By comparing models, flood hazard map shows that multiple river confluence point of both the districts are mostly falling under very high flood hazard zone. The flood data collected from National Remote Sensing Centre (NRSC) was used for validation. The Area Under the Curve” of the “Receiver Operating Characteristic” curve (AUC-ROC), the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Techniques observed the accuracy of 0.835 (83.5%) and 0.752 (75.2%), respectively. This study demonstrated that both models performed well for mapping the flood hazards in the study area, although the AHP model performed better overall.