Objective A systematic review was performed to examine the risk prediction models for prolonged mechanical ventilation in patients after coronary artery bypass grafting (CABG), in order to provide references for clinical practice and related research. Methods A systematic search was conducted in databases including PubMed, Embase, Web of Science, CNKI, and Wanfang Data to identify studies related to risk prediction models for prolonged mechanical ventilation in patients after CABG. The search was conducted from database inception to December 31, 2022. Two researchers independently screened and extracted data, and the prediction model risk of bias assessment tool was used to evaluate the bias and applicability of the included literature. Results A total of 8 articles were included, consisting of 5 studies on the development of prediction models and 3 studies on the validation of prediction model efficacy. Conclusion The predictive efficacy of risk prediction models for prolonged mechanical ventilation in patients after CABG is generally moderate, with an overall high risk of bias. Future efforts should focus on constructing locally applicable prediction models with low bias risk based on large sample data.