Aim: To propose a simple model for predicting preeclampsia (PE) in the 1st trimester of pregnancy on the basis of maternal characteristics (MC) and mean arterial pressure (MAP). Methods: A prospective cohort was performed to predict PE between 11 and 13+6 weeks of gestation. The MC evaluated were maternal age, skin color, parity, previous PE, smoking, family history of PE, hypertension, diabetes mellitus and body mass index (BMI). Mean arterial blood pressure (MAP) was measured at the time of the 1st trimester ultrasound. The outcome measures were the incidences of total PE, preterm PE (delivery <37 weeks) and term PE (delivery ≥37 weeks). We performed logistic regression analysis to determine which factors made significant contributions for the prediction of the three outcomes. Results: We analyzed 733 pregnant women; 55 developed PE, 21 of those developed preterm PE and 34 term PE. For total PE, the best model was MC+MAP, which had an area under the receiver operating characteristic curve (AUC ROC) of 0.79 [95% confidence interval (CI)=0.76–0.82]. For preterm PE, the best model was MC+MAP, with an AUC ROC of 0.84 (95% CI=0.81–0.87). For term PE, the best model was MC, with an AUC ROC of 0.75 (0.72–0.79). The MC+MAP model demonstrated a detection rate of 67% cases of preterm PE, with a false-positive rate of 10%, positive predictive value of 17% and negative predictive value of 99%. Conclusion: The MC+MAP model showed good accuracy in predicting preterm PE in the 1st trimester of gestation.