Context: Pregnancy represents a critical period in a woman's life, where her health significantly impacts the well-being of both herself and her newborn baby. This abstract summarizes a comprehensive analysis of the health status of pregnant women and newborn babies, aiming to identify key factors influencing maternal and newborn health outcomes.

Objective: The main objective of our project is to determine whether a newborn baby is safe or not by diagnosing the health of the mother by examining important features such as Age, Systolic BP, Diastolic BP, Body Temperature, and Heart Rate, along with the Risk Level, according to health records based on previous patients. Early detection of diseases to enable timely interventions and improve treatment outcomes; accurate risk assessment for individuals based on medical history and lifestyle factors; and personalized strategies and treatment plans for individuals based on reports are important. Breastfeeding: The analysis will discuss the numerous benefits of breastfeeding for both mother and baby, including the improved infant immunity and reduced risk of chronic diseases. Strategies for promoting and supporting breastfeeding will be explored. The impact of postpartum depression on both mothers and newborns will be addressed. The importance of mental health screening and providing mothers with the necessary support will be emphasized.

Material/Methods: In this article, we have used statistical analysis techniques to analyze the collected data. Machine learning algorithms were utilized to identify patterns and relationships between maternal health factors and newborn outcomes. Feature selection methods were applied to determine the most significant predictors of maternal and newborn health.

Conclusion: This comprehensive analysis sheds light on the critical factors influencing maternal and newborn health outcomes during pregnancy. Promoting and supporting breastfeeding emerge as crucial strategies for enhancing the health and well-being of both mother and baby.