Preterm Premature Rupture of Membranes (PPROM) represents a significant cause of neonatal morbidity and mortality, with early detection being critical for improved outcomes. Fetal fibronectin (fFN) is a well-established biomarker predictive of preterm birth, including PPROM. In this study, we propose a novel integration of blockchain technology with predictive modeling to enhance data integrity, accessibility, and clinical decision-making for PPROM risk. Using a dataset comprising fibronectin test results and maternal clinical variables, we developed a predictive framework that simulates how blockchain can securely store and share this data across institutions. The system incorporates smart contracts to trigger alerts in cases of high risk. Results demonstrate that integrating predictive analytics with blockchain architecture ensures better data transparency, traceability, and collaborative diagnostics. This work presents a proof-of-concept demonstration highlighting the feasibility and potential of secure, decentralized architectures for future perinatal care applications.