Childhood obesity represents a global public health challenge. This study employs artificial intelligence (AI) to enhance decision-making in pediatric interventions against obesity. A predictive model was developed using data from children participating in an obesity intervention program at the Pediatric Service of the Elx-Crevillent Health Department to identify which type of patient achieves a successful outcome after a standard obesity intervention. The results demonstrate the potential of AI to improve personalized healthcare and optimize resources in combating childhood obesity, specifically in defining which patients may benefit from standard procedures and which patients may require additional resources to achieve improvements. This pilot research contributes to a deeper understanding of the factors related to childhood obesity and lays the groundwork for future AI-driven innovations in pediatric health.