Genome-wide association studies (GWAS) have revolutionized the understanding of genotype-phenotype associations in maize, a crop with extensive genetic diversity and rapid linkage disequilibrium (LD). This review highlights the advancements and future prospects of GWAS in maize, focusing on yield, quality, and environmental stress resilience. GWAS has identified numerous genetic loci and candidate genes associated with complex traits, including responses to both abiotic and biotic stresses. These findings enhance breeding strategies by improving adaptability and yield. The integration of omics data, such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics, has enriched the understanding of complex traits, contributing to the development of more resilient and productive maize varieties. Despite its benefits, GWAS faces challenges such as the impact of environmental factors on gene expression and the need for robust statistical methods to control for population structure. Future research should prioritize functional validation of candidate genes and field evaluations to address these challenges and advance maize molecular breeding programs.Genome-wide association studies (GWAS) have revolutionized the understanding of genotype-phenotype associations in maize, a crop with extensive genetic diversity and rapid linkage disequilibrium (LD). This review highlights the advancements and future prospects of GWAS in maize, focusing on yield, quality, and environmental stress resilience. GWAS has identified numerous genetic loci and candidate genes associated with complex traits, including responses to both abiotic and biotic stresses. These findings enhance breeding strategies by improving adaptability and yield. The integration of omics data, such as genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics, has enriched the understanding of complex traits, contributing to the development of more resilient and productive maize varieties. Despite its benefits, GWAS faces challenges such as the impact of environmental factors on gene expression and the need for robust statistical methods to control for population structure. Future research should prioritize functional validation of candidate genes and field evaluations to address these challenges and advance maize molecular breeding programs.