Crop simulation models are essential tools to facilitate the evaluation and application of crop production practices under different climate scenarios. The present study analyzed the impact of climate change on wheat production in the semi-arid regions of western India by using the decision support system for the agrotechnology transfer (DSSAT-CERES) simulation model. We used ensemble and bias correction data of the coordinated regional downscaling experiment for South Asia (CORDEX-SA) driving global climate model (GCM) experiments for the future climate. The study considered the historical (1981-2010), experimental period (2014-2017), and future (2021-2050 and 2051-2080) climatic data to simulate grain yield. We used a randomized complete block design for different crop treatments, followed by a comparison of the simulated crop yield with the historical yield to evaluate the selected adaptation measures to reduce the impact of future climate scenarios. We observed that early sowing dates and medium planting density were the significant factors for achieving high wheat production. The simulation results revealed that the wheat yields would decrease in the near and far future under RCP 4.5 and RCP 8.5 scenarios. Our findings emphasize the requirement to adapt best measurements to improve yield, which involves early sowing by two weeks and maintaining a planting density of 150 plants per square meter. Experimentally, our results suggest that the DSSAT model, if calibrated carefully, can serve as a valuable tool for decision-making on adaptation practices of winter wheat under changing climates. [GRAPHICS]