Floods are among the most destructive natural hazards affecting Mediterranean watersheds, causing significant environmental, economic, and social impacts. This study aims to assess flood vulnerability in the Oued Bounouara watershed (northeastern Algeria) by integrating Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP). Seven flood-conditioning factors, namely altitude, slope, precipitation, land use, lithology, stream proximity, and flow accumulation, were weighted using the AHP method and integrated through a GIS-based Weighted Overlay approach to produce a flood vulnerability map. The resulting map classified the watershed into five vulnerability classes and revealed that approximately 34% of the study area falls within the High and Very High vulnerability categories, mainly concentrated in the western sector and along the main hydrographic network. The predictive performance of the model was evaluated using an independent validation database consisting of 360 reference points, including 180 documented flood occurrence points and 180 non-flood points compiled from Civil Protection records, municipal archives, historical reports, previous technical documents, and field investigations. Validation results demonstrated that the proposed GIS–AHP model achieved good predictive capability, with 100% of the documented flood occurrences located within the High and Very High vulnerability classes. The Success Rate Curve (SRC) analysis produced an Area Under the Curve (AUC) value of 0.795, indicating good predictive performance, while the Success Curve Area Ratio (SCAR = 2.94) confirmed a strong concentration of flood occurrences within highly vulnerable areas. Sensitivity analysis further demonstrated the robustness of the model under moderate variations in the thematic weights. The proposed GIS–AHP framework provides a reliable, transparent, and transferable approach for flood vulnerability assessment and represents an effective decision-support tool for land-use planning, flood mitigation, infrastructure management, and disaster risk reduction in Mediterranean watersheds and other data-scarce regions.