Preterm birth continues to be one of the major causes of neonatal morbidity and mortality, and the ability to identify pregnancies at the highest risk continues to be hampered by the inadequate understanding of the placental pathophysiology involved. This study seeks to identify the placental dysregulation of angiogenic markers as a potential unifying explanation to the molecular imbalance, structural placental abnormalities, and poor birth outcome(s). Integrated longitudinal profiling of circulating maternal angiogenic markers (anti- and pro-angiogenic), placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and their derived ratios, was combined with the quantitative assessments of placental vascular and histopathological architecture. Structural assessments reported less vascular density, simplified branching networks, and one of the hallmark pathological features of villi in preterm placentas, which closely correlates with anti-angiogenic dominance. Based on these biological insights, the generated predictive models, using machine learning angiogenic + clinical parameters, provided a high level of non-linear risk stratification for preterm birth, which was better than the clinical predictors for discrimination and calibration. Overall, the findings provided evidence for angiogenic dysregulation as a quantifiable and actionable driver for the risk of preterm birth, and also demonstrated the predictive potential of angiogenic profiling for early, targeted obstetric intervention and precision risk assessment.