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Description: Abstract: The use of Artificial Intelligence in recognizing pediatric emotion has gained a central interest with high potential for effective results on children and adolescents. Artificial intelligence is a science that designs systems to perform tasks that need human intellect, such as recognition of patterns, decision-making, and interpretation of data. Applications of artificial intelligence are rapidly growing in the field of health care. In pediatrics, AI technologies have been applied to early disease diagnosis, treatment optimization, and monitoring of neonates to decrease clinical errors and increase precision in care. More directly, the application of AI in recognizing emotions will provide new opportunities for overcoming the difficulties that may have developed in the ability to express emotions of children due to cognitive, physical, or emotional reasons, all of which may delay the timely detection of problems in their mental health. One such promising area is via AI analysis of child behavior, facial expressions, and other non-verbal elements that could offer an understanding of children's emotional states and thereby provide the caregivers, parents, and educators with valuable information to design more targeted interventions. Furthermore, it has been promising how AI systems are capable of recognizing emotions in children with intellectual and multiple disabilities, thus enhancing communication and care. This study aims to map the existing literature on AI applications in recognizing emotions in children and adolescents, evaluating its applicability in clinical settings. Methods: A scoping review will be conducted following the Joanna Briggs Institute guidelines. The research will be carried out in PubMed, Scopus, CINAHL Complete, MEDLINE Complete, IEEE Xplore and Wiley Online Library, without temporal restrictions. Studies in English, Portuguese and Spanish that address the use of AI for emotion recognition in pediatric health contexts will be included. Study selection will be performed by two independent reviewers, and data will be extracted using a standardized form. Discussion: We expect to identify and synthesize the AI technologies applied to emotion recognition in pediatrics, highlighting their clinical applications, gaps in the literature, and implications for clinical practice. The review will contribute to understanding the potential and limitations of AI in emotion recognition within pediatric settings, providing a basis for future research and the development of clinical practices.