〔Abstract〕 To identify the independent risk factors for pyloric lymph node (PLN) metastasis in patients with upper gastric cancer (UGC) and to construct a nomogram prediction model applicable for UGC patients. Methods Clinical data of UGC patients treated at The First Affiliated Hospital of Anhui Medical University (n=721) and The First Affiliated Hospital of Anhui Medical University North District (n=102) between January 2020 and November 2023 were retrospectively 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 discriminative ability and calibration were assessed using receiver operating characteristic (ROC) curves and calibration 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=1.307, 95%CI: 1.038-1.646), T3 stage (OR=5.703, 95%CI: 1.271-25.581), T4 stage (OR=7.827,95%CI: 1.569-39.037), lymphovascular invasion (LVI) (OR=6.637,95%CI: 1.387- 31.574), differentiation extent (OR=3.160, 95%CI: 1.567-6.373), and fibrinogen degradation product (FDP) level (OR=4.565, 95%CI: 1.927-10.810) 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.