Ibadan, one of the largest cities in West Africa, experiences recurrent flood hazards, causing severe damages to lives and properties. Although various flood susceptibility models have evolved to mitigate flood hazards in different parts of the world, model performances vary according to the peculiarity of the study area and conditioning factors. Therefore, specialized studies are essential to determine model performances for specific locations. This study develops an integrated spatial multi-criteria decision-making model to classify flood susceptibility in Ibadan, Nigeria. For the improvement of the weighting accuracy of the flood causative criteria, Fuzzy AHP (FAHP) was integrated with GIS for the weight computation and overlay process. Ten flood causative factors were evaluated using the AHP and FAHP models. Results indicate rainfall, runoff, and distance to stream as the most significant flood causative factors with FAHP and AHP weights of 22, 18, 16, and 23, 23, 18, respectively. The FAHP and AHP maps identified the southern region as the most susceptible, with the FAHP also highlighting the susceptibility of the central region. The models� accuracies were validated by overlaying the AHP and FAHP maps with locations of previous flood occurrences in the study area. The Fuzzy AHP map had a 91 alignment with the historical flood locations while the AHP model produced a 45 match, confirming the higher accuracy of the FAHP model and suitability for flood susceptibility mapping in Nigeria and other West African cities. © 2020, Springer Nature B.V.