Precipitation plays a pivotal role in the evolution of the ecosystems. Many watersheds in Pakistan and particularly in parts of Sindh are ungagged, which urge to estimate the precipitation and other parameters using feasible models for effective planning and management of water resources. Regression analysis is usually employed to understand the hydro-climatic relationships of a watershed. The present study is aimed to investigate the relationship between precipitation and elevation through developing linear regression models for various levels of precipitation data and map their spatial variability in the KNR (Khirthar National Range), Sindh, Pakistan. The precipitation data of 7 meteorological stations covering the study area were used with DEM (Digital Elevation Model) data of 90 m resolution for altitudinal trend analysis. The results of the linear regression model showed a close relationship between the precipitation of various time-scales and elevation, i.e. coefficient of determination R2 values ranging within 0.82060.9604. The correlation was significant at P<0.05 for mean annual, mean monthly, and mean seasonal (Rabi) precipitation. The spatial variation in precipitation was between 127.78-697.98 mm at annual and from 10.84-58.09 mm at mean monthly level. The lapse rate of increase in precipitation with elevation was 27.03 mm per 100 m for annual and 2.24 mm per 100 m for monthly level. At seasonal level, precipitation varied from 24.17-137.87 mm during Rabi (winter) and between 105.78-525.36 mm during Kharif (summer) season. Similarly, the monsoon precipitation (July-September) ranged between 92.24359.93 mm in the study area. The higher precipitation estimated over elevated areas of the region at seasonal and annual levels needs to be harvested through adopting adequate water management techniques for improving agriculture productivity in the downstream areas.