Objective This study aims to construct and validate a nomogram for predicting postoperative survival probability in patients with gastric cancer. Method A retrospective analysis was conducted on 370 patients diagnosed with gastric cancer who underwent radical surgery at Liaoning Cancer Hospital between January 2017 and May 2021. Stratified sampling method was used to divide the data into a training cohort n = 246 and a validation cohort n = 124 at a 2 ∶ 1 ratio. Clinical data including baseline characteristics prognostic nutritional index PNI pathological features inflammatory factors and tumor markers were collected as candidate variables. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent risk factors associated with postoperative survival dependent variables . Subsequently a nomogram prediction model was developed based on these identified factors. The performance of the nomogram—including its accuracy and discriminative ability—was evaluated using the area under the receiver operating characteristic curve AUC calibration curves and compared against that of the traditional TNM staging system. Additionally decision curve analysis DCA and Kaplan-Meier survival curves were employed to further assess its clinical utility. Result Cox regression analyses identified four independent prognostic factors PNI lymph node metastasis depth of invasion and CA125 levels. These factors were incorporated into the nomogram for visual representation of survival predictions. The nomogram demonstrated significantly superior prognostic performance compared to traditional TNM staging this was evidenced by higher AUC values improved calibration through calibration plots and greater net clinical benefit as determined by DCA. Conclusion The nomogram incorporating nutritional indicators—including PNI—can accurately predict postoperative survival in patients with gastric cancer thereby providing a reliable tool for personalized clinical decision-making.