Objective To develop and validate a nomogram model that integrates systemic inflammatory markers to predict the likelihood of pelvic lymph node metastasis （PLNM） in prostate cancer patients prior to surgery. Methods This study retrospectively analyzed the clinical data and preoperative inflammatory markers—including neutrophil?to?lymphocyte ratio （NLR）， platelet?to?lymphocyte ratio （PLR）， systemic immune?inflammation index （SII）， and monocyte?to?lymphocyte ratio （MLR）—of patients diagnosed with prostate cancer. Univariate and multivariate logistic regression analyses were conducted to identify markers that were significantly associated with PLNM. Based on the results of the multivariate analysis， a nomogram was developed and its predictive accuracy was assessed using receiver operating characteristic curves （ROC） and calibration plots. Results Among the 334 enrolled patients with prostate cancer， 107 were identified with PLNM. Univariate analysis revealed statistically significant differences in free prostate?specific antigen （fPSA）， Gleason score， NLR， PLR， MLR， and SII between the PLNM and non?pelvic lymph node metastasis （NPLNM） groups （P < 0.05）. Multivariate analysis confirmed that fPSA， Gleason score， and SII were independent predictors of PLNM （P < 0.05）. A nomogram incorporating these predictors exhibited strong discriminative ability， with an area under the ROC curve （AUC） of 0.79 （95%CI： 0.73 ~ 0.84）. Calibration analysis further demonstrated good consistency between the predicted and observed probabilities of PLNM. Conclusions This study successfully developed a nomogram model based on systemic inflammatory markers for preoperative prediction of pelvic lymph node metastasis in prostate cancer. Owing to its user?friendly design and high predictive accuracy， this tool may serve as a valuable complementary method to conventional imaging techniques， thereby supporting personalized treatment decision?making.