The thesis explores how skeletal maturity assessments improve orthodontic diagnosis and treatment outcomes. It reviews various methods used to evaluate bone maturity, including hand-wrist radiographs, cervical vertebral maturation, CBCT imaging, third molar development, and biomarkers in body fluids. These techniques help determine optimal treatment timing, especially during growth spurts, to enhance treatment efficiency and stability. The thesis emphasizes challenges like variability among individuals and limited predictive power of current methods, and it advocates for integrating AI technologies to improve precision. Overall, it underlines the value of a patient-specific, growth-aware approach in orthodontics.