ObjectiveTo systematically review the research status of risk prediction models for cognitive impairment in patients with T2DM. MethodsThe CNKI, WanFang Data, VIP, CBM, PubMed, Embase, Web of Science, Cochrane Library databases and Clinical trial registration platform were electronically searched to collect relevant literature on risk prediction models for cognitive impairment in patients with T2DM from inception to February 13th 2025. Two researchers independently screened the literature, extracted data, and assessed the risk of bias of the included studies, and then qualitative description and meta-analysis was performed. ResultsA total of 20 studies were included, involving 25 risk prediction models. In terms of the risk of bias, 20 studies were considered as high risk. With regards to applicability, 20 studies were high applicability. The pooled area under the curve (AUC) for modeling set was 0.83 (95%CI 0.79 to 0.88) and for the validation set was 0.83 (95% CI 0.79 to 0.87). It suggested that the model had good discrimination ability. The most common predictors included age, education level, duration of diabetes and depression. ConclusionThe overall performance of the risk prediction model for cognitive impairment in patients with T2DM is good, but the quality of the model needs to be improved.