This study aims to project and characterize the climate extremes in Ravi River Basin (RRB) which is considered a data-poor transboundary basin located in India and Pakistan. Performance of the three GCDs against observation data was evaluated at three stations. A quantile mapping technique was used to correct the biases of four regional climate models (RCMs) and climate extremes were analysed for future period (2020–2095). Seven temperature and rainfall-based indices that represent warm and wet characteristics of climate were chosen. Four statistical parameters and spatial maps were evaluated for the base period 1982–2005. The CPC-NOAA and PU had the best performance for temperature and rainfall data regarding the time series analysis. The quantile mapping improved three important aspects of the climate cycle; the transitions from dry to wet and wet to dry seasons and peaks as well. At spatial scale, quantile mapping well captured the spatial distribution of the eleven indices other than RX1Day, CWD and FD0. The results show that warm and wet extremes will increase in future at 5% significance level across the entire basin with large changes in northeast. The changes will be large for RCP8.5 scenario compare to RCP4.5 scenario and choice of the scenarios has dominant contribution in uncertainty than choice of the models.