ABSTRACTRegionalization of extreme rainfall is useful for various applications in hydro‐meteorology. There is dearth of regionalization studies on extreme rainfall in India. In this perspective, a set of 25 regions that are homogeneous in 1‐, 2‐, 3‐, 4‐ and 5‐day extreme rainfall is delineated based on seasonality measure of extreme rainfall and location indicators (latitude, longitude and altitude) by using global fuzzy c‐means (GFCM) cluster analysis. The regions are validated for homogeneity inL‐moment framework. One of the applications of the regions is in arriving at quantile estimates of extreme rainfall at sparsely gauged/ungauged locations using options such as regional frequency analysis (RFA). TheRFAinvolves use of rainfall‐related information from gauged sites in a region as the basis to estimate quantiles of extreme rainfall for target locations that resemble the region in terms of rainfall characteristics. A procedure forRFAbased onGFCM‐delineated regions is presented and its effectiveness is evaluated by leave‐one‐out cross validation. Error in quantile estimates for ungauged sites is compared with that resulting from the use of region‐of‐influence (ROI) approach that forms site‐specific regions exclusively for quantile estimation. Results indicate that error in quantile estimates based onGFCMregions andROIare fairly close, and neither of them is consistent in yielding the least error over all the sites. The cluster analysis approach was effective in reducing the number of regions to be delineated forRFA.