Objective To explore the development and validation of a prediction model for severe communi-ty-acquired pneumonia in adults based on peripheral blood inflammatory indicators.Methods Venous blood samples of 204 community-acquired pneumonia in adults patients admitted to 7 hospitals in Chongqing area from April 2021 to August 2022 were collected to detect C-reactive protein(CRP),peripheral white blood cell count(WBC),neutrophil to lymphocyte ratio(NLR),cytokines,lymphocyte subgroups and neutrophil CD64 index.All of patients were divided into a training group and a validation group according to the time of admis-sion.Univariate and multivariate Logistic regression were used to analyze the data of the training group,the characteristic factors of severe progression for pneumonia were selected to construct the nomogram model,and the data of the validation group was used to verify the model.The receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis(DCA)were used to evaluate the prediction ability of the model for severe community-acquired pneumonia in adults.Results Logistic regression analysis showed that age,CRP,WBC,interleukin(IL)-4/interferon gamma ratio and IL-6/IL-10 ratio were independent risk factors for severe community-acquired pneumonia in adults.The area under the ROC curve of the nomogram model in the training group and the validation group was 0.893 and 0.880,respectively.The calibration curve and DCA results shown that the model had a good prediction effect for severe community-acquired pneumonia in adults.Conclusion The inflammatory indicators included in this model are simple and easy to obtain clinically.This model with good differentiation and accuracy,it can be used as a practical tool to predict severe community-ac-quired pneumonia in adults,and has certain clinical application value.