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Description: This scoping review aims to comprehensively investigate the existing body of lit-erature concerning the integration of AI in pediatric dentistry. The focus is on delving into re-cent advancements and the transformative possibilities that this technology holds, with a specific emphasis on its potential to enhance dental health outcomes for children. The present scoping review will follow the guidelines of the Joanna Briggs Institute (JBI)Br for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extensions for scoping reviews (PRISMA-ScR). We developed a key research question to guide our search for strategies. The answer to this question could be used by pediatric dentists as a reference: “What are the current developments and challenges in the application of artificial intelligence in pediatric dentistry?”. Eligibility criteria This review selectively incorporates original research articles that delve into the appli-cation of AI models in the realms of pediatric dentistry and pedodontics. To maintain focus and rigor, incomplete texts, scoping reviews, narrative reviews, case series, con-sensus conferences and articles written in languages other than English have all been excluded from consideration, such as studies including adults. Moreover, there was no restriction in the year of publication of the studies. This meticulous approach ensures a thorough examination of substantive and pertinent research contributions in the speci-fied field. Information Sources and Search Strategy To assess the corpus of current literature on the subject, a few database searches were carried out through December 2023. The development of a search strategy that incor-porated all discovered keywords and free-standing terms was aided by a health scienc-es librarian. The Web of Science, Embase, Scopus, and PubMed databases were utilized. To confirm the validity of every source of evidence listed in the reference list, addition-al research was looked into. The outcomes of modifying the approach search for every database are shown in Supplementary Table 1. Study selection Following the acquisition of search results from every electronic database, the citations were imported into EndNote X9, a reference manager program developed by Clari-vateTM, London, UK. Reports that were duplicates were eliminated, and articles that provided updates or preliminary findings were only assessed once. Two writers, V.R. and S.L.R., checked all of the titles and abstracts they had gathered from the databases before reading the full texts of any relevant studies. The eligibility of the studies was evaluated objectively, and any disagreements were settled after discussion with anoth-er author, G.P. Using Cohen kappa statistics, the degree of agreement between the two reviewers was assessed. Data extraction In order to gather the characteristics and outcomes (study design, sample size, and ob-jectives) needed for the ensuing literature analysis, two authors (S.L.R. and V.R.) creat-ed a data extraction form. We had discussed any discrepancies with G.P., another au-thor reviewer. Cohen kappa statistics was employed to evaluate the degree of concur-rence between the two authors. Information synthesis The methodology employed in reporting the findings of this study is derived from es-tablished frameworks delineated in prior research conducted by other scholars (14, 18). In order to enhance relevance to clinical indications, the observations were systemati-cally categorized and discussed within distinct domains. These domains were meticu-lously structured to encompass all the pertinent data extracted from the studies incor-porated in the analysis. This approach ensures a systematic and comprehensive presentation of the research outcomes, building upon the foundations laid by previous scholarly investigations.