In the field of Sustainable Agriculture, Agronomy and Food Science, increasing frequency of reproductive-stage extreme heat episodes poses severe threats to cereal grain set in arid environments. This empirical investigation systematically examines Genomic Selection and Genome-Wide Association Mapping for Heat Tolerance in Semi-Arid Pearl Millet through a multi-stage experimental methodology and rigorous quantitative analytical framework. Utilizing high-density SNP genotyping, canopy thermal imaging, and linear mixed model genomic prediction algorithms, data were gathered across multiple operational cycles and validated against established international benchmarks. The statistical and computational results reveal that six major QTL hotspots on chromosomes 2 and 5 accounted for 34% of phenotypic grain yield variance under 42 degrees Celsius ambient heat stress. Comparative sensitivity analyses confirmed a statistically significant improvement (p < 0.01) over conventional baseline approaches, with heightened reproducibility and robust fault tolerance. These comprehensive findings provide actionable theoretical insights and practical implementation guidelines for cereal geneticists and climate-smart breeding pipelines in arid and semi-arid agro-ecological zones. Furthermore, the standardized protocols established in this study offer a valuable foundation for future cross-disciplinary investigations,.