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BACKGROUND Chronic obstructive pulmonary disease (COPD) is a major public health concern. Early detection and prevention interventions are crucial. Artificial intelligence (AI) developed to predict COPD risk. Tele-pulmonary rehabilitation (Tele-PR) shows promise in improving outcomes. However, its preventive efficacy in individuals at risk of COPD remains unexplored. OBJECTIVE To examine the effectiveness of a Tele-PR program on exercise capacity, disease-related symptoms, muscular strength, and COPD risk rate in individuals at risk of COPD based on AI predictions. METHODS Of 286, 38 individuals at risk of COPD from AI predictions were eligible and allocated to either an intervention or control group (20 and 18 per group). The intervention group received a Tele-PR program, consisting of the exercise regimen three times per week for twelve weeks. The control group was given verbal information about the disease and prevention advice for self-management. Outcomes were exercise capacity measured by a six-minute walk test (6MWT), disease-related symptoms measured by the modified medical research council dyspnea (mMRC) scale and COPD assessment test (CAT), back and leg strength measured by a dynamometer, and COPD risk rate evaluated by AI predictions. All outcome measures were assessed at baseline and after the 12-week intervention. RESULTS All participants completed the trial with no adverse events reported. At the end of the 12-week training, the Tele-PR group demonstrated significantly greater improvements in six-minute walk distance (6MWD), lower COPD risk rate than the control group (p = .011 and .024, respectively). There were no significant differences in other outcome measures. CONCLUSIONS The twelve-week Tele-PR program effectively improves exercise capacity and diminishes rate of COPD risk in individuals at risk of COPD predicted from the AI approach. CLINICALTRIAL None

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