International Research Journal of Education and Technology

The Maternal Predictive Risk Analysis System uses a Random Forest model to classify pregnancy risk based on eight clinical indicators, including blood pressure and glucose. Integrated with a Flask backend, the platform features a Care Hub for symptom tracking, medication reminders, and SOS alerts, bridging the gap between patients and clinicians. By centralizing longitudinal medical records and providing real-time risk notifications, the system shifts maternal care from reactive visits to a proactive, data-driven ecosystem. This lightweight solution improves early risk visibility and accelerates clinical response times to ensure safer outcomes for mothers and infants.

Keywords: Maternal health, Pregnancy risk prediction, Random Forest, Flask, Care coordination, Explainable AI, SOS alerts, Care Hub