Objective To systematically evaluate the prediction models of multidrug-resistant organism (MDRO) infection in patients in the intensive care unit (ICU). Methods Literatures related to the prediction models of MDRO infection in ICU patients were retrieved from PubMed, Embase, Web of Science, Cochrane Library, CINAHL, CBM, Wanfang, and China National Knowledge Infrastructure (CNKI) from the establishment of the databases up to June 2022. Two researchers independently screened the literatures, extracted data, and evaluated the risk of bias and applicability. Results A total of 17 literatures were included, and the area under the receiver operating characteristic curve of all 16 models were >0.7 (0.64-0.94). Risk of bias assessment showed high risk of bias in all included models, but the models were all applicable. The most common identified predictive factors in the models included antimicrobial drugs, mechanical ventilation, length of ICU stay, indwelling urinary catheter, gender, underlying diseases, and comorbidities. Conclusion The existing predictive models for MDRO infection in ICU patients are not ideal, as they exhibit bias in the development, design, statistical analysis, and reporting of the models. In the future, attention should be focused on the methodological details of research design and the standardization of reports. Additionally, larger-scale, multicenter studies and model validation and updates should be con-ducted to improve model performance.