This study focuses on flood susceptibility mapping in Damaturu, Yobe State, Nigeria, leveraging Geographic Information Systems (GIS) and remote sensing techniques. Damaturu is prone to recurring flood events, necessitating effective flood mitigation and risk assessment strategies. Through the integration of GIS and remote sensing data, this research develops a robust flood susceptibility model. The study incorporates various data sources, including digital elevation models, hydrological data, and land-use maps, to create a comprehensive spatial database. Remote sensing data obtained from satellite and aerial platforms facilitate land cover change detection, flood extent identification, and flood-related damage assessment. The flood susceptibility mapping process employs GIS-based techniques, such as Analytical Hierarchy Process (AHP) and Weight of Evidence (WoE), to analyze and integrate the datasets, ultimately generating flood susceptibility maps for the area. These maps offer essential insights into flood-prone regions, aiding in flood risk assessment, disaster preparedness, and the development of targeted flood management strategies. The research outcomes are invaluable for policymakers, urban planners, and emergency response teams, enabling informed decision-making and proactive flood mitigation measures. The integration of GIS and remote sensing technologies ensures a comprehensive and adaptable approach to combat the challenges posed by floods in Damaturu, enhancing the resilience of local communities to future flood events.