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Developmental differences are broadly implicated, but particular vulnerability factor interactions are poorly understood. This study sought to identify moderators of OUD relapse between age groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This secondary analysis compared young adults (18\u201025) to older adults (26+) from a comparative effectiveness trial (\u201cXBOT\u201d) that randomized (<jats:italic>N<\/jats:italic>\u2009=\u2009570) participants to extended\u2010release naltrexone or sublingual buprenorphine\u2010naloxone. We explored the relationship between 25 prespecified patient baseline characteristics and relapse to regular opioid use by age group and treatment condition, using logistic regression.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Young adults (<jats:italic>n\u2009<\/jats:italic>=\u2009111) had higher rates of 24\u2010week relapse than older adults (<jats:italic>n\u2009<\/jats:italic>=\u2009459) (70.3% vs 58.8%) and differed on a number of specific characteristics, including more smokers, more intravenous opioid use, and more cannabis use. No significant moderators predicted relapse, in either three\u2010way or two\u2010way interactions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions and Scientific Significance<\/jats:title><jats:p>No baseline factors were identified as moderating the relationship between age group and opioid relapse, nor any interactions between baseline characteristics, age group, and treatment condition to predict opioid relapse. Poorer treatment outcomes for young adults are likely associated with multiple developmental vulnerabilities rather than any single predominant factor. Although not reaching significance, several characteristics (using heroin, smoking tobacco, high levels of depression\/anxiety, or treatment because of family\/friends) showed higher odds ratio point estimates for relapse in young adults than older adults. This is the first study to explore moderators of worse OUD treatment outcomes in young adults, highlighting the need to identify predictor variables that could inform treatment enhancements. 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