Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, and traditional preventive measures focus on lifestyle modifications, pharmacologic interventions, and risk stratification. Recently, imaging has emerged as an interesting tool in cardiovascular prevention. This review explores the role of various imaging modalities in early detection, risk assessment, and disease monitoring. Noninvasive techniques such as carotid ultrasound, arterial stiffness assessment, echocardiography, and coronary artery calcium scoring enable the identification of subclinical atherosclerosis and ventricular dysfunction, providing insights that complement conventional risk factors. Coronary computed tomography angiography and cardiac magnetic resonance offer high-resolution visualization of vascular and myocardial pathology, contributing to refined risk stratification. Furthermore, emerging markers such as epicardial adipose tissue and hepatic steatosis are gaining recognition as potential predictors of cardiovascular risk. Advancements in artificial intelligence (AI) are revolutionizing cardiovascular imaging by enhancing image interpretation, automating risk prediction, and facilitating personalized medicine. Future research should focus on optimizing the integration of imaging into clinical workflows, improving risk prediction models, and exploring AI-driven innovations. By exploiting imaging technologies, clinicians could enhance primary and secondary prevention strategies, ultimately reducing the global burden of CVDs.