Abstract: Objective To explore the establishment of a risk-predicting model with nomogram for acute kidney injury(AKI) in critically ill pregnant women. Method 320 critically ill pregnant women were divided into the AKI group and non-AKI group, and the basic information and clinical data of all patients were retrieved. Logistic regression analysis was used to analyze the independent risk factors of AKI in critically ill pregnant women. The selected independent risk factors were used to establish a nomogram prediction model with R software, and the predictability and accuracy of the model will be verified. Result Logistic regression analysis of the general clinical data of the two groups showed that hypertension(OR= 2. 509,95% CI:1. 412-4. 459), liver function damage(OR=2. 741,95% CI:1. 542-4. 870), increased lactic acid(OR= 2. 920,95% CI:1. 650-5. 166), shock(OR= 7. 171,95% CI:2. 431-21. 152), APACHE Ⅱ score(OR= 2. 352,95% CI:1. 274-4. 341), SOFA score(OR= 5. 189,95% CI:2. 812-9. 576) ere independent risk factors for AKI in critically ill pregnant women, with statistical difference(P< 0. 05), all of which were highly correlated with critical maternal AKI. Based on these six independent risk factors for AKI(hypertension, liver function damage,shock, elevated lactate, APACHE II score and SOFA score), a nomogram model for predicting the risk of AKI in critically ill pregnant women was established an verified. The predicted values are basically consistent with the measured values, indicating that the nomogram model of this study has better predictive ability. Meanwhile, Bootstrap internal verification method was used to verify AKI in critically ill pregnant women, the C-index index is as high as 0. 829(95%CI: 0. 801-0. 857), indicating that the nomogram model of this study has good quality precision and discrimination.Conclusion Full consideration of factors as hypertension, liver function damage, shock, elevated lactate, APACHE II score and SOFA score in critically ill pregnant women can assess the incidence of AKI in this population comprehensively;it can improve the diagnostic efficiency of AKI in critically ill pregnant women. The model can be applicated actively in clinical medicine and deserves to be promoted.