ObjectiveTo establish a predictive model for neck lateral lymph node metastasis (LLNM) in unilateral papillary thyroid cancer (uni-PTC) with central lymph node metastasis (CLNM). MethodsThe uni-PTC patients with CLNM were included in this study. The patients underwent thyroid surgery in the 960th Hospital of the PLA Joint Logistics Support Force from May 2018 to December 2021, who were randomly divided into the modeling group and the validation group according to the ratio of 7∶3. The risk factors of neck LLNM were analyzed by univariate and multivariate logistic regression and the nomogram of prediction model was constructed. The receiver operating characteristic (ROC) curve and calibration curve were used to validate the prediction model. ResultsA total of 237 patients were included in this study, including 158 patients in the modeling group and 79 patients in the validation group. The LLNM occurred in the 84 patients of the modeling group and 43 patients of the validation group. The multivariate logistic regression analysis was performed according to the statistical indicators in the univariate analysis results of the modeling group and the risk factors considered in the previous studies. The results showed that the patients with maximum diameter of the lesions >1 cm, multiple lesions, extraglandular invasion, the rate of CLNM ≥0.414, and lesions located at the upper portion had higher probability of LLNM (OR>1, P<0.05). The area under ROC curve of the nomogram in predicting LLNM in the modeling group was 0.834 [95%CI (0.771, 0.896)], which in the validation group was 0.761 [95%CI (0.651, 0.871)]. The calibration curve showed a good calibration degree in the prediction model. ConclusionThe clinical risk prediction model established based on the risk factors can better predict the probability of LLNM.