Abstract: Objective To establish and evaluate an individual nomogram model for predicting the risk of renal injury through analyzing the related influencing factors in Henoch Schonlein purpura(HSP) children.Methods From May 2017 to February 2020,a total of 180 hospitalized HSP children were selected as research subjects. Based upon the presence or absence of renal injury,they were divided into two groups of renal injury(n=48) and non-renal injury(n=132). Logistic regression model was utilized for analyzing the related factors of renal injury. Nomogram online website was employed for plotting a nomogram model to predict the risk of renal injury. Receiver operator characteristic curve(ROC),calibration curve and Hosmer-Lemeshow goodness-of-fit test were used for evaluating the nomogram model.Results Logistic regression model indicated that respiratory tract pathogen infection,Epstein Barr virus infection,neutrophil-to-lymphocyte ratio ≥ 6.11,platelet count ≥ 302.16×10⁹/L and D-dimer ≥ 543.07µg/L levels were independent risk factors of renal injury(P<0.05). ROC results showed that the area under cruve(AUC) of predicting the risk of renal injury was 0.882. And calibration curve revealed a straight line with a slope of close to 1. Hosmer-Lemeshow goodness-of-fit test showed χ²=6.627,P=0.577.Conclusions Based upon five independent risk factors of renal injury,including respiratory tract pathogen infection,Epstein Barr virus infection,neutrophil-to-lymphocyte ratio,platelet count,D-dimer levels,nomogram modeling for predicting the risk of renal injury offers decent discrimination and accuracy in HSP children.