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Introduction Emergency departments are facing increasing strain due to overcrowding and resource shortages, leading to the suspension of some services. Stratifying the clinical risk—defined as the severity and likelihood of harm—is crucial for anticipating care needs and supporting decision-making. Implementing predictive models for clinical risk management offers a technological solution to this challenge. This systematic review will evaluate the performance and usefulness of a predictive model for managing the clinical risk of people who visit the emergency department.Methods and analysis Eight electronic databases will be searched (CINAHL Plus, Health Technology Assessment Database, MedicLatina, MEDLINE, PubMed, Scopus, Cochrane Plus Collection, Web of Science). Risk of bias will be assessed using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and Prediction Model Risk of Bias Assessment Tool.Ethics and dissemination Ethical approval is not required. Results will be disseminated through peer-reviewed publications.PROSPERO registration number CRD42024556926.