Understanding the ramifications of climate change on Lahore City involves a complex interplay of climatic variables and the city's susceptibility to these shifts. To assess these implications comprehensively, this study scrutinizes data from three Global Climate Models (GCMs) within the Coupled Model Inter-comparison Project phase 6 (CMIP6): BCC-CSM 2-MR, INM CM-5–0, and MPI ESM 1 2 HR, all at a 100-km resolution. The focus is on projected temperature and precipitation changes in Lahore City from 2020 to 2100. Crucial to this analysis is the statistical downscaling of climatic variables, a key process in enhancing the local accuracy of GCMs. Statistical models were developed to bridge the gap between GCMs’ large-scale climate variables and the localized climate data of Lahore. The study assesses the performance of the Climate Model data for hydrologic modeling (CMhyd) software in downscaling maximum and minimum temperature as well as precipitation data for Lahore across three GCMs and three scenarios (SSP126, SSP245, and SSP585). The results showcase a notable improvement in the GCMs’ ability to reproduce Lahore's local climate conditions, particularly in terms of temperature. While the downscaled precipitation data also exhibited reasonable agreement with observed data, performance varied by GCM and scenario. Comparing the future projections to the baseline period (1995–2014), the selected GCMs predict an increase in average monthly rainfall and maximum and minimum temperatures in highlights an estimated increase in precipitation ranging from 10.4% to 14.2% and temperature variations of 0.51 °C to 2.1 °C, underscoring the potential implications of climate change on Lahore City. In summary, this research underscores the effectiveness of the CMhyd software in downscaling climate data at the local level, enhancing the accuracy of GCMs in representing local climate conditions.