Adolescence is a pivotal stage of biopsychosocial transformation involving rapid growth, hormonal shifts, and metabolic adaptation. However, rising obesity rates are threatening children and adolescents worldwide. Healthy growth relies on a synergistic equilibrium between developmental and metabolic homeostasis, regulated by multi-level networks. This chapter outlines key technical challenges and proposes an AI-driven ecosystem integrating multimodal data fusion, dynamic modeling, and pathological simulation to decode these networks. With the integration of life sciences, data science, and engineering technologies, this approach aims to shift pediatric health care from disease treatment to proactive metabolic optimization, supporting children’s full growth potential.