Purpose of Review <p>This review synthesizes current evidence on biomarkers for the prediction of cardiotoxicity.</p> Recent Findings <p>Conventional biomarkers are being reported in new settings. Omics, microRNA, and extracellular vesicles are emerging as new potential biomarker platforms. AI-enabled strategies combine conventional and novel biomarkers to predict cardiotoxicity.</p> Summary <p>The expanding complexity of cancer therapies has driven the need for more accurate tools to monitor cardiovascular health in oncology patients, evolving from basic measures of myocardial injury to sophisticated, multimodal indicators. AI-enabled predictive frameworks integrate recent advances in proteomics, transcriptomics, and metabolomics, with multimodal imaging, including speckle-tracking echocardiography, cardiac magnetic resonance, PET, and CT, for early detection and risk stratification. These tools define a path toward personalized, proactive cardiac care in oncology, for individualized prevention, earlier diagnosis, and therapy modification in cancer survivors at risk of cardiovascular disease.</p>