Climate change poses an increasing threat to agricultural productivity in the Texas High Plains (THP), a semi-arid region facing both warming trends and declining groundwater resources. This study integrates process-based crop modeling with geospatial analysis to identify spatial zones of climate vulnerability and adaptive potential for four major crops; winter wheat, cotton, maize, and grain sorghum under future climate scenarios. Using the Decision Support System for Agrotechnology Transfer (DSSAT) model, historical (1991–2020) and future yields (2031–2060 and 2070–2099) were simulated across 48 counties under Representative Concentration Pathway 4.5 and 8.5 (RCP 4.5 and RCP 8.5). Spatial clustering techniques, including Global Moran’s I and Getis-Ord Gi* statistics, were applied to classify counties into vulnerable, adaptive, stable, and more stable zones based on projected yield changes. Results revealed that wheat vulnerability was concentrated in southern counties, with projected yield decreases of 10–30% under RCP 8.5 relative to the 1991–2020 baseline. In contrast, northern counties showed yield increases of 30–50% under RCP 4.5 by mid-century and under RCP 8.5 by end-century. Cotton yields are projected to increase by 20–40% across most counties under both RCP 4.5 end-century and RCP 8.5 mid- and end-century relative to the historical baseline, although localized vulnerability may emerge in southwestern THP under RCP 8.5 by end-century. For grain sorghum yields are projected to increase by 10–20% in eastern and northern counties under RCP 4.5, but under RCP 8.5 widespread yield declines exceeding 40% are expected by end-century. These reductions are largely attributed to reduced rainfall and increased temperature stress during the growing season. In this study, sorghum was planted in June, which may have exposed the crop to greater late-season heat stress; earlier planting dates could potentially mitigate some of these adverse effects. Maize, which was planted in April in this study, showed spatially variable yield changes, with several southern counties exhibiting positive trends. These localized yield increases are primarily associated with projected precipitation increases during the maize growing season compared to the historical baseline, rather than an inherent crop-specific resilience to climate change. These spatially explicit findings underscore the need for targeted adaptation strategies, including the deployment of climate-resilient crop varieties, optimized irrigation management, crop diversification, and adaptive land use planning. The study offers actionable insights to support climate-resilient agricultural planning and inform precision adaptation policies for sustaining crop productivity in the THP under future climate scenarios.