Myopia has become a major visual disorder among school-aged children in East Asia due to its rising prevalence over the past few decades and will continue to be a leading health issue with an annual incidence as high as 20%-30%. Although various interventions have been proposed for myopia control, consensus in treatment strategies has yet to be fully developed. Atropine and orthokeratology stand out for their effectiveness in myopia progression control, but children with rapid progression of myopia require treatment with higher concentrations of atropine that are associated with increased rates of side effects, or with orthokeratology that carries risk of significant complication. Therefore, improved risk assessment for myopia onset and progression in children is critical in clinical decision-making. Besides traditional prediction models based on genetic effects and environmental exposures within populations, individualized prediction using machine learning and data based on age-specific refraction is promising. Although emerging treatments for myopia are promising and some have been incorporated into clinical practice, identifying populations who require and benefit from intervention remains the most important initial step for clinical practice.