Objective To analyze the risk factors for hypothermia occurring within 24 hours of hospitalization in premature infants to construct a risk prediction model, and to provide a reference for clinical intervention measures to prevent hypothermia in hospita-lized premature infants. Methods A total of 307 premature infants were randomly divided into a training set (215 cases) and a validation set (92 cases) in a 7∶3 ratio. The occurrence of hypothermia (axillary temperature <36.5℃) in hospitalized premature infants and its influencing factors were analyzed, and a nomogram was developed to evaluate its discriminative ability and consistency. Results Among the 307 premature infants, 209 cases (146 in the training set and 63 in the validation set) experienced hypothermia upon hospitalization, resulting in an incidence rate of 68.08%. Logistic regression analysis in the training set revealed that low birth weight, early preterm birth, an Apgar score of ≤7 at 5 minutes, and the presence of neonatal respiratory distress syndrome were independent risk factors for hypothermia in hospitalized premature infants. The area under the ROC curve for the training set was 0.809 (95%CI:0.744-0.875), the calibration curve slope was close to 1, and the Hosmer-Lemeshow goodness-of-fit test showed χ2=8.761, P=0.363. In the validation set, the area under the ROC curve was 0.844 (95%CI:0.755-0.933), with a calibration curve slope close to 1, and the Hosmer-Lemeshow test showed χ2=7.911, P=0.442. Conclusion The incidence rate of hypothermia in hospitalized premature infants is relatively high. It is essential to pay attention to high-risk premature infants with low birth weight, early preterm birth, an Apgar score of ≤7 at 5 minutes, and concurrent neonatal respiratory distress syndrome. The constructed risk prediction model demonstrates good predictive performance and can be used to identify the risk of hypothermia in hospitalized premature infants at an early stage.