Objective: This study seeks to identify clinicopathological risk factors associated with tumor deposits (TD) development in stage I-III gastric cancer patients and to construct a visualized predictive model for clinical application. Methods: A retrospective cohort of 1,284 gastric cancer patients treated at the Affiliated Hospital of Hebei University (September 2010-September 2022) was analyzed. Patients were stratified into training (n = 963) and validation (n = 321) cohorts via simple randomization at a 3:1 ratio. Lasso regression analysis was employed to screen variables, followed by multivariate logistic regression to establish an individualized nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis (DCA). Results: TD-positive patients (n = 224) exhibited significantly reduced overall survival and disease-free survival compared to TD-negative counterparts (n = 1,060, p < 0.05). Multivariate logistic regression analysis confirmed tumor size (OR = 1.26; 95% CI 1.01-2.21), elevated CEA (OR = 2.04; 95% CI 1.02-3.16), elevated CA199 (OR = 1.007, 95% CI:1.003-1.011), and pN stage (OR = 3.22; 95% CI 2.12-4.34) as independent predictors of TD occurrence (all p < 0.05). The nomogram demonstrated robust discriminative capacity, with AUC values of 0.803 (95% CI 0.751-0.894) and 0.864 (95% CI 0.725-0.917) in the training and validation cohorts, respectively. Calibration plots revealed excellent agreement between predicted and observed probabilities. DCA further validated the model's clinical utility, showing superior net benefits across threshold probabilities of 1-99%. Conclusion: This TD-specific nomogram, incorporating tumor size, serum biomarkers (CEA/CA199), and pathological staging (pN), provides a clinically applicable tool for preoperative risk stratification and personalized therapeutic decision-making in stage I-III gastric cancer.