Systemic lupus erythematosus (SLE) patients are vulnerable to infections. We aim to explore the approach to differentiate active infection from disease activity in pediatric SLE patients. Fifty pediatric SLE patients presenting with 185 clinical visits were collected. The associations between both clinical and laboratory parameters and the outcome groups were analyzed using generalized estimating equations (GEEs). These 185 visits were divided into 4 outcome groups: infected-active (n = 102), infected-inactive (n = 11), noninfected-active (n = 59), and noninfected-inactive (n = 13) visits. Multivariate GEE (generalized estimating equation) analysis showed that SDI, SLEDAI-2K, neutrophil-to-lymphocyte ratio (NLR), hemoglobin, platelet, RDW-to-platelet ratio (RPR), and C3 are predictive of flare (combined calculated AUC of 0.8964 and with sensitivity of 82.2% and specificity of 90.9%). Multivariate GEE analysis showed that SDI, fever temperature, CRP, procalcitonin (PCT), lymphocyte percentage, NLR, hemoglobin, and renal score in SLEDAI-2k are predictive of infection (combined calculated AUC of 0.7886 and with sensitivity of 63.5% and specificity of 89.2%). We can simultaneously predict 4 different outcome with accuracy of 70.13% for infected-active group, 10% for infected-inactive group, 59.57% for noninfected-active group, and 84.62% for noninfected-inactive group, respectively. Combination of parameters from four different domains simultaneously, including inflammation (CRP, ESR, PCT), hematology (Lymphocyte percentage, NLR, PLR), complement (C3, C4), and clinical status (SLEDAI, SDI) is objective and effective to differentiate flares from infections in pediatric SLE patients.