BackgroundAnxiety and depression pose a significant global health challenge for elderly individuals. Research has demonstrated the potential of traditional Chinese medicine (TCM) exercise therapies in alleviating these conditions. However, ongoing debate and uncertainty persist regarding the optimal therapy and its impact on anxiety and depression. This study aims to evaluate and prioritize TCM exercise therapies for anxiety and depression in older adults, to identify the most effective intervention, and to provide a basis for informed decision-making in clinical practice.MethodsWe conducted a comprehensive search of electronic databases including The Web of Science, PubMed, the Cochrane Library, China National Knowledge Infrastructure (CNKI), Wang Fang, and Wei Pu database up to July 2022. Two researchers independently reviewed all included studies and extracted relevant data. Traditional meta-analysis was performed using Review Manager version 5.4, while network meta-analysis was conducted using STATA software version 15.1 to generate network evidence plots and funnel plots.ResultA total of 30 trials, involving 2,806 participants, met the eligibility criteria. The traditional meta-analysis revealed that TCM exercise significantly improved anxiety (SMD = −0.82, 95% CI = −1.39, −0.26, p = 0.004) and depression (SMD = −0.63, 95% CI = −0.85, −0.41, p < 0.01) compared to the control group. In the network meta-analysis, Tai Chi exercise was ranked as the most effective intervention for anxiety (68.3%), followed by Yi Jin Jing (63.6%). For depression, the Tai Chi exercise was ranked as the most effective (87.8%), followed by the Ba Duan Jin exercise (74.1%).ConclusionTCE exercise can improve anxiety and depression in older adults, Among the four TCE exercise therapies included, Tai Chi exercise showed better efficacy than other types of treatment. Nevertheless, further research is required to validate the effectiveness of this exercise therapy through larger and more rigorous clinical trials.Systematic review registrationhttp://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023438697.