Objective To develop and externally validate a multidimensional Early Warning Scoring Scale （SEWS） for pediatric sepsis， grounded exclusively in routinely available laboratory parameters reflecting four pathophysiological domains： infection， coagulation dysfunction， impaired tissue perfusion， and depletion of host physiological reserves. Methods We conducted a retrospective cohort study involving 193 children with confirmed infection admitted to Shenzhen Children′s Hospital between January 2021 and December 2023. Participants were stratified into two clinically defined groups： the sepsis group （n = 92） and the non-sepsis infection group （n = 101）， based on consensus diagnostic criteria （e.g.， International Pediatric Sepsis Consensus Conference definitions）. Comparative analyses of baseline laboratory parameters were performed between groups. Candidate variables were initially selected using univariate analysis and area under the receiver operating characteristic curve （AUC-ROC） evaluation； subsequently， independent predictors of pediatric sepsis were identified via multivariable logistic regression. A weighted scoring scale—the SEWS—was derived directly from regression coefficients. Internal model performance was rigorously assessed， and external validation was carried out using an independent cohort of 40 consecutive cases collected prospectively from January to April 2024. Results Multivariable logistic regression identified six independent predictors of pediatric sepsis： Procalcitonin （PCT）， international normalized ratio （INR）， myoglobin， albumin， hemoglobin （Hb）， and mean platelet volume （MPV） （all P < 0.05）. The composite prediction model achieved an AUC of 0.983 （95%CI： 0.969 - 0.997）， significantly outperforming any single biomarker. The SEWS demonstrated excellent discriminative ability in the derivation cohort： sensitivity = 94.6%， specificity = 92.1%， and AUC = 0.981 （95%CI： 0.967 - 0.995） at an optimal cutoff score of ≥ 6 points. In the external validation cohort （n = 40）， SEWS maintained high sensitivity （100%） and strong specificity （84.0%）. Conclusions The SEWS is a pragmatic， multidimensional clinical tool built solely on routinely measured laboratory parameters. It exhibits robust diagnostic accuracy for early identification of pediatric sepsis， with a score of ≥ 6 conferring high positive predictive value. This evidence supports its integration into clinical workflows to facilitate timely risk stratification and prompt therapeutic intervention.