Flooding is an inevitable but natural process that happens over the period of time; it not only endangers people’s health, wealth, and assets, but it has also a negative impact on a country’s economy. Hence, effective flood management is required in order to minimize the influence of flooding on human lives and livelihoods. The aim of this research is to use a frequency ratio model (FRM) to identify flood-susceptibility areas in the city of Kolhapur. The research was conducted in two parts. Initially, field-survey data was used to create a flood-inventory map. There were 255 flood locations identified throughout the research region; of these, 178 locations (70%) were used for training data, and 77 (30%) were used for verification purposes. The spatial database was then used; from this, ten flood contributing parameters were generated: slope, elevation, rainfall, distance from a river, a stream power index (SPI), a topographical wetness index (TWI), a topographical roughness index (TRI), a plan curvature and profile curvature, and land use/land cover. Finally, an FR model database was created for flood-susceptible mapping. The prepared database was separated into four flood-susceptibility zones: low susceptibility, medium susceptibility, high susceptibility, and very high susceptibility. About 26.08% of the land was classified as ‘very high susceptibility,’ while 21.18% was classified as ‘high susceptibility.’ The final flood-susceptibility map was verified by using the receiver operating characteristic (ROC) curve. The results indicated that the method that was used in this study provided accurate results (with a success rate of 87%); this indicated an acceptable result for our flood-susceptibility zonation. Local administrations, researchers, and planners will benefit greatly from this flood-susceptibility analysis in developing flood-prevention plans.