ObjectiveTo systematically review the risk prediction models for the occurrence of low anterior resection syndrome in patients with rectal cancer after surgery. MethodsThe PubMed, Web of Science, Embase, Cochrane Library, Scopus, CINHAL, CNKI, CBM, WanFang Data and VIP databases were electronically searched to collect studies related to the objectives from inception to June 13, 2023. Two reviewers independently screened the literature, extracted data using the critical appraisal and data extraction for systematic reviews of prediction modelling studies (CHARMS) checklist, and assessed quality of the included studies using prediction model risk of bias assessment tool (PROBAST). ResultsA total of 14 studies were included, all studies reported model discrimination, and 10 studies reported calibration. The models were internally validated in 8 studies, externally validated in 5 studies. The most common predictors included in the models were tumour distance from the anal verge, neoadjuvant therapy, anastomotic leak and BMI. Only 5 studies had good overall applicability, and all studies had a high risk of bias, with the risk of bias mainly stemming from the field of participants, outcomes and analysis. ConclusionThere are still many shortcomings in the risk prediction models for the occurrence of low anterior resection syndrome in patients with rectal cancer after surgery. Future studies may consider external validation and recalibration of existing models. New prediction models should be built and validated according to methodological guidelines.