Computational biology is revolutionizing healthcare by integrating advanced computational techniques with biological data to enhance clinical decision support. By analyzing vast datasets, including genomic, transcriptomic, proteomic, and clinical information, computational biology enables personalized medicine, tailoring treatments to individual patients based on their unique genetic and molecular profiles. It facilitates early disease diagnosis through predictive models, identifies genetic risk factors, and uncovers therapeutic targets for complex diseases like cancer and cardiovascular conditions. Multi-omics approaches provide a comprehensive understanding of biological systems, revealing the interplay between molecular layers and improving the accuracy of diagnoses and treatment strategies. Additionally, computational tools simulate patient-specific disease phenotypes, predict drug responses, and optimize clinical trials. These advancements empower clinicians with data-driven insights to make informed decisions, ultimately improving patient outcomes. Despite challenges in data integration and ethical considerations, computational biology continues to push the boundaries of precision medicine and personalized healthcare.