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Objectives APS is a systemic autoimmune disorder marked by thrombotic and non-thrombotic manifestations. In children, diagnosis remains challenging due to lack of validated pediatric criteria. As the 2006 revised Sapporo has been used without validation, and the 2023 ACR-EULAR criteria aim to improve sensitivity by including non-thrombotic features are yet to be validated in this populationThis study evaluates the performance of the ACR-EULAR APS criteria in a pediatric cohort of APS and aPL patients, focusing on key diagnostic parameters and comparison with traditional criteria.Methods A retrospective review of 69 patients‘ <19 years followed at the Sheba Medical Center (2011–2024) was conducted. Clinical, laboratory, and serological data including anti-cardiolipin, anti-b2GPI, lupus anticoagulant, as well as APS score (aGAPSS) were analyzed. Patients were divided to APS patients (n=29) or aPL carriers (controls ; n=40). APS diagnosis was made based on expert opinion and validated by 2 independent experts.Results In our cohort (mean age 16 y; 62% female) APS diagnosis was more common among those with a family history of APS (37.5% vs. 17.5% ; p= 0.056). Comparing APS patients and aPL carriers, arterial (Odds ratio 109 CI95% 8.58-1404) and venous thromboses (Odds ratio 96.6 CI95% 14.7-632.7) were the strongest predictors of APS. Moreover, non- thrombotic manifestation and elevated aGAPSS scores correlated with APS diagnosis. Catastrophic APS rate was 10.3% among our APS group. Mortality rate was 6.7% among APS group and 0% among aPL carriers. In this pediatric population the 2023 ACR-EULAR criteria exhibited higher sensitivity (96.6%) compared to the 2006 criteria (87.1%) while specificity was similarly high in both.Conclusions Pediatric APS features familial predisposition as well as thrombosis, and microvascular involvement, with high autoantibody positivity being common. The ACR-EULAR classification criteria’s superior sensitivity supports their use for assessment of the pediatric population; further validation is needed to optimize clinical application.