To explore the predictive value of high definition flow imaging (HD-Flow) in detecting different systolic parameters of M1 segment of the fetal middle cerebral artery (MCA) for fetal distress (FD) in preeclampsia (PE). Methods: A total of 120 PE patients who underwent HD-Flow detection in our hospital from June 2019 to June 2023 were selected as the study objects. They were divided into NFD group (n=64) and FD group (n=56) according to whether FD occurred. The clinical data and systolic parameters of distal M1 segment and proximal 1/3 of M1 segment were compared between the two groups. LASSO logistic regression analysis model screened the potential factors of FD, multivariate Logistic regression analysis of the risk factors affecting the occurrence of FD. The risk prediction model of FD occurrence was constructed and verified. The predictive ability of each index to FD occurrence. The receiver operating characteristic (ROC) curve was plotted and the area under the curve (AUC) was calculated to analyze the predictive value of different systolic parameters for the occurrence of FD. Results: LASSO regression analysis screened out 15 predictors, and Logistic analysis results showed that, gestational age, intrauterine infection, gestational diabetes mellitus, PCO2, RI, PI, PSV and S/D at the distal and mesial 1/3 of M1 segment were independent risk factors for FD. Construct a FD risk prediction model, the area under the curve (AUC) before and after ROC curve verification were 0.801 (95%CI: 0.696~0.845) and 0.785 (95%CI: 0.688~0.829), respectively, indicating good model differentiation and high accuracy. Gestational age, intrauterine infection, gestational diabetes mellitus and PCO2 indexes were added to the systolic parameters at the distal and mesial 1/3 of M1 segment in MCA, and the prediction ability was the best. The prediction performance of RI at the far end of M1 and S/D at the near 1/3 of M1 is high, and the PI, PSV and S/D at the far end of M1 and the PI and PSV at the near 1/3 of M1 have certain prediction value. Conclusion: Systolic parameters of different M1 segments in fetal MCA can predict the occurrence of FD to a certain extent, and RI and S/D at the distal part of M1 segment and near 1/3 of M1 segment have high predictive performance. The establishment of a risk prediction model for FD can be used to accurately predict the risk of FD in PE patients and provide targeted intervention for prevention and treatment.