Primary parotid squamous cell carcinoma (pPSCC) is a rare salivary gland neoplasm. Due to the low incidence of pPSCC, there is a lack of clinical studies with large samples. The aim of this study was to identify prognostic factors and develop a nomogram for predicting overall survival (OS) and cancer specific survival (CSS) of pPSCC, with the goal of guiding clinical decision making. We identified eligible pPSCC patients from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly allocated to either the training or validation cohort in a 7:3 ratio. The X-tile software was utilized to determine the optimal cut-off values for age at diagnose, regional nodes examined, regional nodes positive, and tumor size, and changes continuous variables into categorical variables. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors. Based on the identified variables, two nomograms were developed and validated to predict the 1-, 3-, and 5-year OS and CSS of pPSCC. The accuracy of the prediction was evaluated using the C-index and calibration curve. Decision curve analysis (DCA) and receiver operating characteristic (ROC) were utilized to compare the nomogram with the American Joint Committee on Cancer (AJCC) stage system in order to assess its superiority. Furthermore, two risk stratification systems were established based on the constructed nomograms. From 2000 to 2019, a total of 2,187 pPSCC patients were screened from the SEER database. The incidence of pPSCC showed an overall upward trend, with the highest incidence in patients aged 71-80 years. The 495 patients with pPSCC ultimately identified from the SEER database were randomly allocated into a training cohort (n = 348) and a validation cohort (n = 147).Five independent prognostic variables were identified for OS, including age at diagnose, distant metastasis, AJCC stage, type of surgery, and tumor size. However, six independent prognostic variables were identified for CSS, with the addition of regional lymph node positivity as an additional variable. Nomograms of OS and CSS were established based on the results. In the training cohort and the validation cohort, the C-index of OS and CSS was 0.679, 0.677, 0.650 and 0.650 respectively. Calibration curve demonstrate that the predictions of 1-, 3-, and 5-year survival probability models for OS and CSS were generally consistent with actual observations in both the training cohort and the validation cohort. Our nomogram demonstrated a superior clinical net benefit compared to the AJCC 7th version, as indicated by DCA and ROC analysis. Additionally, patients were stratified into low-, middle-, and high-risk groups based on the nomogram risk score. The Kaplan-Meier curve demonstrated significant differences in survival among the three groups. In this study, new nomograms and risk classification systems were successfully developed to predict the 1-, 3-, and 5-year OS and CSS of pPSCC patients, which has good accuracy and superiority and can help doctors and patients make clinical decisions.