Para-aortic lymph node (PALN) metastasis of patients with locally advanced cervical cancer (LACC) is associated with multiple risk factors. This study aimed to identify risk factors and develop a predictive model for PALN metastasis based on the pathological diagnosis via surgical staging to determine the patient-population suitable for extended-field irradiation (EFRT) and clarify the prognosis of patients with LACC. Five parameters were identified as predictors by logistic regression analysis. The predictive model was displayed as a nomogram and then modified into a simple scoring system. The concordance indices for the prediction nomogram were 0.939 in the training cohort, and 0.954 in the validation cohort, respectively. The scoring system consisted of tumor size, histological type, number of pelvic lymph nodes (PLNs), common iliac lymph node, and shorter diameter of the largest PLN. With a cutoff value of 8 points, the sensitivity and specificity of the predictive model were 91.04% and 85.37%, respectively, in the training cohort, and 89.47% and 84.68%, respectively, in the validation cohort. Using this system, patients were divided into high- and low-risk groups. Patients in the high-risk group showed a greater likelihood of PALN metastasis and worse PFS and OS than those in the low-risk group. The predictive model displays promise for the pathological diagnosis of PALN via surgical staging, offering good accuracy. It provides a non-invasive, practical tool to guide precise radiation strategy and stratify prognosis of patients with LACC.