Abstract: Objective To establish a nomogram prediction model for renal damage in children with IgA vasculitis (IgAV), in order to provide an efficient and simple method for predicting IgAVN in children. Methods A total of 240 children with IgAV who were treated at Department of Pediatrics, Suqian Hospital of Nanjing Drum Tower Hospital Group from January 2022 to December 2023, were included for retrospective analysis. The subjects were randomly divided into a training set (n=168) and a test set (n=72) in a 7∶3 ratio. Univariate and multivariate logistic regression analyses were performed to identify the factors influencing the prediction of IgAVN. A nomogram model was established, and the model's discrimination was evaluated by plotting a receiver operating characteristic (ROC) curve. Results Statistical differences were found between the IgAV group and the IgAVN group in terms of age, white blood cell (WBC) count, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), complement C3, complement C4, high-sensitivity C-reactive protein (hs-CRP), and blood urea nitrogen (BUN) (all P<0.05). Variables identified as significant in the univariate logistic regression were included in the multivariate logistic regression model. The results showed that age, WBC, PLR, C3, C4, hs-CRP, and BUN were independent factors influencing the prediction of IgAVN (P<0.05). Based on these factors, a nomogram model was established. For the training set, the area under the curve (AUC) of the nomogram was 0.955 (95% CI:0.923-0.986), with a sensitivity of 82.14% and a specificity of 93.75%. For the test set, the AUC was 0.917 (95% CI:0.848-0.985), with a sensitivity of 70.83% and a specificity of 95.83%. DeLong test for AUC differences between the training and test sets showed no statistical difference in predictive performance (D=0.990, P=0.324>0.05). Conclusions The nomogram model based on age, WBC, PLR, C3, C4, hs-CRP, and BUN demonstrates high clinical value in predicting IgAVN and can be widely applied in clinical practice.