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Melanie C Matheson,1,2,* Gayan Bowatte,1,3,* Jennifer L Perret,1,4 Adrian J Lowe,1,2 Chamara V Senaratna,1,5 Graham L Hall,6–8 Nick de Klerk,6,8 Louise A Keogh,9 Christine F McDonald,4 Nilakshi T Waidyatillake,1 Peter D Sly,10 Deborah Jarvis,11,12 Michael J Abramson,13 Caroline J Lodge,1,2,* Shyamali C Dharmage1,2,* 1Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia; 2Murdoch Children’s Research Institute, Melbourne, VIC, Australia; 3National Institute of Fundamental Studies, Kandy, Sri Lanka; 4Department of Respiratory and Sleep Medicine, Institute for Breathing and Sleep, Austin Health, University of Melbourne, Melbourne, VIC, Australia; 5Department of Community Medicine, University of Sri Jayewardenepura, Nugegoda, Sri Lanka; 6Telethon Kids Institute, Perth, WA, Australia; 7School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia; 8Centre of Child Health Research, University of Western Australia, Perth, WA, Australia; 9Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia; 10Child Health Research Centre, The University of Queensland, Brisbane, QLD, Australia; 11MRC-PHE Centre for Environment and Health, Imperial College London, London, UK; 12Population Health and Occupational Diseases, National Heart and Lung Institute, Imperial College London, London, UK; 13School of Public Health & Preventive Medicine, Monash University, Melbourne, VIC, Australia *These authors contributed equally to this work Abstract: Early identification of people at risk of developing COPD is crucial for implementing preventive strategies. We aimed to systematically review and assess the performance of all published models that predicted development of COPD. A search was conducted to identify studies that developed a prediction model for COPD development. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies was followed when extracting data and appraising the selected studies. Of the 4,481 records identified, 30 articles were selected for full-text review, and only four of these were eligible to be included in the review. The only consistent predictor across all four models was a measure of smoking. Sex and age were used in most models; however, other factors varied widely. Two of the models had good ability to discriminate between people who were correctly or incorrectly classified as at risk of developing COPD. Overall none of the models were particularly useful in accurately predicting future risk of COPD, nor were they good at ruling out future risk of COPD. Further studies are needed to develop new prediction models and robustly validate them in external cohorts. Keywords: COPD, early detection, predictors and risk prediction models