Objective To develop a prediction model for lower limb deep venous thrombosis (DVT) in critically ill patients and to evaluate the predictive validity. Methods A total of 420 critically ill patients were divided into two parts:300 cases for model development and 120 cases for verification. Logistic regression analysis was performed to identify risk factors and formulate prediction model. Bootstrap method was used for internal validation of the model, and 120 cases for external validation of the model. Results Logistic regression analysis showed that plasma D-dimer, mechanical ventilation, venous thromboembolism history, vasopressor use and diabetes were independent risk factors for lower limb DVT in critically ill patients. The area under ROC curve was 0.935 in internal validation and 0.925 in external validation. Hosmer-Lemeshow test showed P=0.901. Conclusion The nomogram established in this study for prediction of lower limb DVT in critically ill patient population has good predictive performance and strong operability, which is conducive to early screening and diagnosis.