Artificial Intelligence (AI) has become an independent discipline and is impacting various fields, including orthodontics. With the paradigm shift toward precision medicine, research on Deep Learning (DL) will keep increasing within the orthodontic specialty. DL is utilized to facilitate diagnostics, treatment planning, digital workflow and by providing predictive insights. The current research aim is to present a comprehensive bibliometric analysis for visualizing and mapping research on DL in orthodontics shedding light on this research area. Bibliometric parameters were extracted and 171 articles were retrieved from the Scopus database with no initial time limit. Research visualization and mapping was performed using VOSviewer and Rstudio. The results provide a current overview of the research landscape, including bibliographic coupling of authors, keyword analysis, citations analysis, and emerging trends, providing insights into the state of DL research in orthodontics. The majority of research originated from China and The United States. Peking University Hospital was the institution with the highest number of publications, and Xu T. was identified as the leading author in the field. The primary focus of DL research in orthodontics has been in the areas of cephalometry, anatomic landmark detection, extractions planning and diagnostic imaging.