<p>Psychotherapy dropout represents a persistent challenge in mental healthcare delivery. This study presents the first comprehensive bibliometric analysis mapping the intellectual structure and evolution of dropout research, utilizing 861 publications indexed in the Web of Science Core Collection from 1961 to 2024. Employing performance analysis and science mapping techniques, including citation analysis, keyword co-occurrence, and burst analysis, we identified key developmental trajectories, thematic hotspots, and emerging frontiers. Results indicate a consistent growth in research output, largely quantitative in nature and predominantly led by the United States. Key research hotspots include dropout within specific clinical populations (particularly post-traumatic stress disorder, eating disorders, and substance use disorders), the extensive focus on dropout related to Cognitive Behavioral Therapy (CBT), and the pivotal role of the therapeutic alliance, highlighting the need for tailored retention strategies. Notably, the application of machine learning for predicting dropout emerged as a significant and rapidly advancing research frontier. This data-driven overview underscores critical needs for future research, including refining dropout’s operational definition, integrating qualitative methodologies to complement quantitative findings, increasing focus on real-world effectiveness studies, and enhancing cross-cultural perspectives beyond Western, Educated, Industrialized, Rich, and Democratic contexts. This bibliometric analysis provides valuable guidance for researchers and clinicians aiming to address psychotherapy retention challenges and improve treatment outcomes.</p>