Pre-eclampsia is a complicated hypertensive pregnancy condition that has a major effect on the health of both the mother and the fetus and puts the affected women at risk for long-term cardiovascular (CV) problems. Despite advances in understanding its etiology, early detection of pre-eclampsia and its associated CV risks remains challenging. This mini-review emphasizes the critical role of biomarkers and advanced diagnostic techniques in addressing this gap. Emerging biomarkers, including angiogenic factors (soluble fms-like tyrosine kinase-1/placental growth factor ratio), metabolic and lipidomics markers, inflammatory cytokines, and exosomal components, provide promising pathways for early identification and risk stratification. Diagnostic techniques can be further improved by classifying these biomarkers according to their capacity to predict long-term CV risks. Technological advancements, such as omics platforms, molecular imaging, wearable health devices, and artificial intelligence (AI) and machine learning, further improve real-time detection and personalized management of pre-eclampsia. By focusing on biomarker-centric predictors of CV risks, this review highlights the integration of multi-biomarker panels and AI-driven algorithms to optimize risk prediction. The transition from association to action is explored, with an emphasis on translating knowledge into effective prevention strategies and improved risk assessment protocols. Structured postpartum follow-up is advocated to monitor and mitigate long-term CV risks in pre-eclamptic women. Practical applications, including targeted interventions and personalized risk management strategies, are discussed. By bridging cutting-edge research and clinical practice, this review aims to enhance maternal health outcomes and advance preventative measures for CV diseases in women with a history of pre-eclampsia.