Objective: To investigate the risk factors for pulmonary infection during chemotherapy in patients with small cell lung cancer(SCLC)and to develop and validate a risk prediction model. Methods: Patients with SCLC who received chemotherapy at the First Affiliated Hospital of Nanjing Medical University from April 2020 to March 2022 were retrospectively enrolled as the training cohort(n=251), and a prospective cohort of SCLC patients was consecutively included as the validation cohort(n=112). According to follow-up outcomes, patients were divided into the pulmonary infection and non-infection groups. In the training cohort, univariate and multivariate logistic regression analyses were performed to identify independent risk factors and to construct a scoring model. The discriminative ability of the model was evaluated using the receiver operating characteristic(ROC)curve, and calibration was assessed using calibration curves. The model was compared with previously reported nomogram models and further validated in the validation cohort. Results: Multivariate logistic regression analysis showed that smoking history, pleural effusion, hoarseness, single-agent chemotherapy, and albumin <35 g/L after the first cycle of chemotherapy were independent risk factorsfor pulmonary infection in patients with SCLC(all P < 0.05). Based on these five variables, the SCLC-PIR scoring model was established. In the training cohort, the area under the curve(AUC)was 0.870(95% CI: 0.818-0.922), with an optimal cutoff value of 5 points, yielding a sensitivity of 71.7% and a specificity of 89.4%. The calibration curve demonstrated good consistency between the infection risks predicted by this model and the actual risks. The predictive performance of the model remained stable when applied to the validation cohort, with an AUC of 0.896(95% CI: 0.832-0.961). Furthermore, the predictive efficacy of this model outperformed previous nomogram models. Conclusion:The SCLC-PIR scoring model, based on smoking history, pleural effusion, hoarseness, single-agent chemotherapy, and post-chemotherapy albumin <35 g/L, shows good discrimination and calibration in predicting pulmonary infection during chemotherapy in patients with SCLC, and may be useful for early identification of high-risk patients.