Background <p>To explore the risk factors for severe pertussis and to develop a classification model for illness severity in hospitalized children with pertussis.</p> Methods <p>A regression analysis was carried out on the cases diagnosed with pertussis in Wuhan Children’s Hospital from January 2022 to October 2024. With April 2024 as the cut-off point, the patients were divided into a training group and a verification group. SPSS and R language were used to analyze the risk factors of severe pertussis in the training group and build a classification model for illness severity in hospitalized children with pertussis.</p> Results <p>Among the relevant predictors, HR, RR, Moist rales, Hb, Alb and IgG are the independent risk factors for severe pertussis. In this study, a nomogram model for illness severity in hospitalized children with pertussis was constructed. Firstly, through training sets, it was confirmed that the prediction model had good discrimination (AUC = 0.935) and calibration (Mean squared error = 0.00062). Finally, the predictive value of the model was further confirmed in the internal validation sets as well (AUC = 0.93, Mean squared error = 0.00089).</p> Conclusion <p>The nomogram constructed in this study provides a clinical tool for assessing severity stratification in hospitalized children with pertussis, guiding the early identification and clinical management of severe cases.</p> Clinical trial number <p>Not applicable.</p>