Since overdiagnosis of beta-lactam (BL) allergy is common in the pediatric population, delabeling is a critical part of antimicrobial stewardship. Undesirable consequences of inaccurate BL allergy labeling can be handled by incorporating traditional delabeling or newer risk-based strategies into antibiotic stewardship programs. Conventional assessment of BL allergy relies upon a stepwise algorithm including a clinical history with skin testing followed by drug provocation tests (DPTs). However, a growing number of studies highlighted the suboptimal diagnostic value of skin testing in children. Recently, there has been a paradigm shift in the practice of BL allergy assessment due to recent challenging data which emphasize the safety and accuracy of direct DPTs in children with a suspicion of non-immediate mild cutaneous reactions such as maculopapular eruption, delayed urticaria, and possibly also for benign immediate reactions such as urticaria/angioedema. Identifying low-risk BL allergy patients, in whom skin tests can be skipped and proceeding directly to DPTs could be safe, has become a hot topic in recent years. New risk stratification and predictive modeling studies that have the potential to better predict BL allergy risk status have recently been introduced into the field of drug allergy, particularly in adults. However, in contrast to adults, risk assessment studies in children are rare, and optimal risk definitions are controversial. In the coming years, promising potential methods to elucidate the predictors of BL allergy in children will require multidimensional approaches that may include predictive analytics, artificial intelligence techniques, and point-of-care clinical decision tools.