Floods are a widespread and damaging natural phenomenon that causes harm to human lives, resources, property and has agricultural, eco-environmental, and economic impacts. Therefore, it is crucial to perform flood susceptibility mapping (FSM) to identify susceptible zones to mitigate and reduce damage. This study assessed the damage caused by the 2022 flash flood in Sindh and identified flood-susceptible zones based on the frequency ratio (FR) and analytical hierarchy process (AHP) models. Flood inventory maps were generated, containing 150 flood sampling points, which were manually selected from Landsat imagery. The flood sampling points were split into 70 % for training and 30 % for validating the results. Furthermore, fourteen flood conditioning factors were considered in the analysis for developing FSM. The final FSM is categorized into five zones, representing levels from very low to very high. The results identified that the areas under very high flood-susceptible zones in Ghotki (FR 4.42 % and AHP 5.66 %), Dadu (FR 21.40 % and AHP 21.29 %), and Sanghar (FR 6.81 % and AHP 6.78 %). Ultimately, FSM accuracy was evaluated using the receiver operating characteristics and area under the curve method, resulting in Ghotki (FR 82 %, AHP 83 %), Dadu (FR 91 %, AHP 90 %), and Sanghar (FR 96 %, AHP 95 %). This study enhances the scientific understanding of flash flood impacts across diverse regions and emphasizes the importance of accurate FSM for informed decision-making. The findings provide important informations and are supportive for policymakers, agricultural planners, and stakeholders engaged in flood risk management to mitigate the adverse consequences of flash floods.