According to a retrospective cohort study, a machine learning model was able to predict the risk of preeclampsia in late pregnancy using routinely collected data. The study included 58,839 pregnancies in three health facilities. Preeclampsia is a multisystem disease affecting 2 to 8% of all pregnant women and is one of the main causes of maternal and fetal mortality.[1] Late preeclampsia occurs in 80 to 95% of all cases of preeclampsia.[2] Preeclampsia pregnancies were associated with a 2- to 3-fold higher risk of perinatal complications, including perinatal fetal death.[3] A model based on machine learning represents a potential tool for early detection of the risk of this serious disease in late pregnancy. Such an approach could allow doctors to better identify pregnant women at higher risk and implement early interventions to prevent the development of the disease.