〔Abstract〕 To investigate the risk factors for wheezing during infancy in preterm infants after discharge and to develop a nomogram model for predicting wheezing. Methods A total of 329 preterm infants were selected for this study. The data were randomly divided into a training set (n = 232) and a validation set (n = 97) in a 7 ∶3 ratio. The training set was further divided into a wheezing group (n = 73) and a non⁃wheezing group (n = 159) based on the occurrence of wheezing. Logistic regression analysis was used to identify independent risk factors for wheezing , and the R software was used to construct and validate the predictive model. Results Compared with the non⁃wheezing group , the wheezing group had significantly lower gestational age , higher rates of mechanical ventila⁃tion , neonatal pneumonia , patent ductus arteriosus within 1 week , pulmonary hypertension , and prolonged antibiot⁃ic use (P < 0. 05) . The independent risk factors for wheezing in preterm infants during infancy included gestational age ( OR : 0. 96 , 95% CI: 0. 95 - 0. 98) , mechanical ventilation ( OR : 11. 08 , 95% CI: 6. 36 - 19. 31) , duration of antibiotic use ( ≥1 week vs < 1 week , OR : 5. 31 , 95% CI: 3. 19 - 8. 84) , 25% tidal volume expiratory flow 22. 58) , neonatal pneumonia ( OR : 4. 79 , 95% CI: 2. 83 - 8. 10) , and frequency of respiratory infections in the first six months ( ≥3 times vs < 3 times , OR : 5. 18 , 95% CI: 3. 10 - 8. 67) ( P < 0. 05) . The areas under the ROC curve (AUC) for the training and validation sets were 0. 889 (95% CI:0. 844 - 0. 934) and 0. 959 (95% CI: 0. 923 - 0. 995 ) , respectively. The calibration curve showed good agreement with the ideal curve , and decision curve analysis demonstrated high net benefit for predicting wheezing. Conclusion The nomogram model based on independent risk factors for wheezing in preterm infants provides a high level of accuracy and may serve as a useful reference for clinical practice.