〔Abstract〕 To identify the independent risk factors for pyloric lymph node（PLN）metastasis in pa- tients with upper gastric cancer（UGC）and to construct a nomogram prediction model applicable for UGC patients. Methods Clinical data of 823 UGC patients attended between January 2020 and November 2023 were retrospec- tively collected. Patients were randomly divided into a training set（n=576）and a validation set（n=247）at a 7：3 ratio. Based on the training set，multivariate Logistic regression analysis was performed to identify independent risk factors for PLN metastasis，and a nomogram prediction model was constructed accordingly. The model ’s dis- criminative ability and calibration were assessed using receiver operating characteristic（ROC）curves and calibra- tion curves. Finally，external validation was conducted using the validation set to evaluate the model ’s stability and generalizability. Results Multivariate Logistic regression analysis revealed that tumor size（ OR=1. 324， 95%CI：1. 053-1. 667），T3 stage（OR=5. 738，95%CI：1. 281-25. 695），T4 stage（OR=7. 680，95%CI：1. 542- 38. 247）， lymphovascular invasion（LVI ）（OR=6. 623，95%CI：1. 384-31. 708）， differentiation extent（OR= 3. 108，95%CI：1. 545-6. 251）， and fibrinogen degradation product（FDP）level（OR=4. 849，95%CI：2. 071- 11. 355）were independent risk factors for PLN metastasis in UGC patients. The nomogram model constructed based on these factors demonstrated areas under the ROC curve（AUC）of 0. 815（95%CI：0. 751-0. 815）in the training set and 0. 832（95%CI：0. 731-0. 933）in the validation set. Calibration curves indicated good agreement between predicted and observed outcomes. Conclusion This nomogram prediction model exhibits good predictive performance for assessing the risk of PLN metastasis in UGC patients.