Background: As many as 60% of pediatric patients taking second-generation antipsychotics (SGA) experience weight gain (antipsychotic-induced weight gain). However, the subgroup that experienced substantial weight increase was poorly understood. This study aimed to identify the development and predictors of clinically significant weight gain (CSWG) among pediatric SGA recipients. Methods: A retrospective analysis of the 2016 to 2021 IQVIA Ambulatory EMR-US database was conducted. The study cohort comprised SGA-naive patients ages 5 to 19, continuously prescribed SGA for ≥90 days. CSWG was defined as a weight gain in BMI z-score >0.5. The development of CSWG was described using the group-based trajectory model approach, and multinomial logistic regression analysis was conducted to examine the risk factors associated with the CSWG trajectories. Results: Of the 16,262 SGA recipients who met the inclusion criteria, 4 distinctive CSWG trajectories were identified: (1) Rapid (14.6%), (2) Gradual (12.6%), (3) Transit (7%), and (4) no CSWG (65.8%). Factors associated with a higher likelihood of having rapid or gradual CSWG versus nonsignificant weight gain were being younger (OR [95% CI] = 12-17 vs. 5-11, Rapid, 0.727 [0.655-0.806]; Gradual, 0.776 [0.668-0.903]), male (Rapid, 1.131 [1.021-1.253]), non-Hispanic White (Black vs. White: Rapid, 0.833 [0.709-0.98]), with lower baseline BMI z-score (Rapid, 0.376 [0.361-0.392]; Gradual, 0.449 [0.424-0.476]), and receiving olanzapine as the initial SGA (Rapid, 1.38 [1.093-1.74]). The Area under the Receiver operating characteristic (ROC) Curve for the comparison of rapid and gradual CSWG with no CSWG trajectory were 0.83 and 0.80, respectively. Conclusions: SGA recipients experienced four distinctive CSWG trajectories (Rapid, Gradual, Transient, and No CSWG). The risk of CSWG could be predicted using patient characteristics at the SGA initiation. This insight highlights the importance of personalized monitoring and timely intervention strategies for at-risk individuals who experienced persistent CSWG in real practice.