The main purpose of this study is to predict early preeclampsia using machine learning algorithms with Particle Swarm Optimization. Preeclampsia is one of the causes of maternal mortality, in the last two decades, there has been no significant decrease in the incidence of preeclampsia. The magnitude of this problem has an impact on the mother during pregnancy and childbirth. The entire population in this study was pregnant women. The entire population in this study was pregnant women. The samples in this study were 504 pregnant women from the medical records of Ansari Saleh General Hospital Banjarmasin in 2022. The algorithm used in this study using eXtreme Gradient Boosting, Adaptive Boosting, Random Forest, Logistic Regression, and for optimization algorithm using Particle Swarm Optimization. Based on the result, Random Forest was the best model with an accuracy rate of 96.08%. The variables that most influence the incidence of preeclampsia are the history of preeclampsia, a history .....

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