Coronary artery calcium (CAC) scoring has emerged as one of the most important imaging biomarkers for cardiovascular risk assessment by providing a quantitative measure of cumulative coronary atherosclerotic burden. Derived from non-contrast cardiac computed tomography using the Agatston method, CAC offers standardized, reproducible, and prognostically robust information that extends beyond traditional risk factors. A large body of evidence demonstrates a graded relationship between increasing CAC scores and adverse cardiovascular outcomes, while a score of zero is associated with low short to intermediate term event risk, although not complete absence of disease. In contemporary cardiology practice, CAC plays a critical role not only in risk stratification but also in therapeutic decision-making, particularly in individuals with borderline or intermediate estimated risk where treatment uncertainty exists. CAC-guided approaches can inform statin initiation, preventive therapy intensity, and, in selected cases, aspirin allocation, while also serving as a potential gatekeeper before coronary computed tomographic angiography (CCTA). However, several important limitations remain, including inability to detect non-calcified plaque, challenges in interpreting serial progression, and reduced CCTA specificity in patients with very high calcium burden due to blooming artifacts. Advances in imaging technology, artificial intelligence–based quantification, and multiparametric plaque assessment are expected to further enhance the clinical utility of CAC in the future. This review provides a comprehensive, clinically oriented synthesis of the biological mechanisms, technical principles, prognostic significance, and practical applications of CAC scoring, with particular emphasis on its integration with CCTA and its role in real-world decision pathways.