According to UNICEF-India, 46% of maternal fatalities and 40% of neonatal fatalities transpire during labor or within the initial 24 h post-delivery. Antepartum care includes routine surveillance, assessment of risks, and appropriate actions to enhance the health of the mother and fetus. Intrapartum care provides for safe labour and delivery with surveillance and appropriate management of complications by skilled personnel. This study aims at identifying the importance of holistic care using emotional intelligence with analytical tools and machine learning models in these stages and how it helps in preventing complications through the identification of high risk pregnancies. The results of the attempts of applying various machine learning models used to define the most important risk factors. The aim is to reduce maternal and neonatal morbidity and mortality. Lack of adequate management of intrapartum care can lead to postpartum problems to a large extent and thus affect the prenatal and fetal well-being.