Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality globally, necessitating effective risk stratification strategies for optimal management and prevention. This narrative review explores the role of laboratory biomarkers in CVD risk assessment, encompassing lipid biomarkers (total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides), inflammatory biomarkers (C-reactive protein, interleukins, tumor necrosis factor-alpha), cardiac biomarkers (troponin, B-type natriuretic peptide, myeloperoxidase), hemostatic biomarkers (fibrinogen, D-dimer), metabolic biomarkers (hemoglobin A1c, insulin, adiponectin, leptin), and genetic biomarkers (apolipoprotein E genotype, familial hypercholesterolemia genes, single nucleotide polymorphisms related to CVD). The utility of individual biomarkers versus multimarker panels, integration of biomarkers into risk assessment models, and their application in specific populations such as women and the elderly are discussed. Challenges including standardization of biomarker measurement, interpretation of biomarker levels, cost-effectiveness, and accessibility are highlighted, along with strategies to overcome bias and confounding factors. Future directions focus on novel biomarkers in the research pipeline, integration of omics technologies (genomics, proteomics, metabolomics), and personalized medicine approaches for enhanced risk prediction and tailored interventions.