Machine learning (ML) is a subsection of artificial intelligence (AI) that develops dynamic algorithms for data-making decisions. Medical science is an area where the application of ML can be very productive. The adoption of ML methods in medical sciences especially in the HELLP Syndrome prediction has been slow. Machine learning techniques have shown promise in predicting various complications of pregnancy, including preeclampsia and preterm birth. However, their application in predicting HELLP syndrome, a rare but serious condition, remains relatively understudied. This study investigates the application of machine learning algorithms to predict HELLP syndrome among pregnant women presenting with preeclampsia. The research population comprises 266 pregnant women between 28 and 38 weeks of gestation, recruited from the gynecology-obstetrics department of Mother and Child Hospital “Saadna Abdenour” in Setif, Algeria, between June 2020 and June 2021. The data collected includes epidemiological, diagnostic, therapeutic, and evolutionary variables, with a focus on severe preeclampsia cases. The results highlight the potential of machine learning algorithms in predicting HELLP syndrome, providing valuable insights for clinical decision-making and improving maternal and neonatal outcomes.