Bioinformatics has emerged as a transformative discipline in agriculture and biological sciences by integrating computational tools with large-scale biological data. The advent of high-throughput sequencing technologies and omics approaches has enabled researchers to analyze genomic, transcriptomic, proteomic, and metabolomic datasets for crop improvement, disease resistance, and sustainable agriculture. This review provides an in-depth analysis of bioinformatics applications in agriculture, including genomics-assisted breeding, stress tolerance, microbial analysis, and precision agriculture. Additionally, the integration of artificial intelligence and machine learning in bioinformatics is discussed. The advantages, limitations, and future prospects of bioinformatics in agriculture are critically evaluated.