Ovarian serous cystadenocarcinoma is a common malignant tumor of female genital organs. Treatment is generally less effective as patients are usually diagnosed in the late stage. Therefore, a well-designed prognostic marker provides valuable data for optimizing therapy. In this study, we analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data. We observed the correlation between gene expression and patients' survival and eventually established a risk assessment model of five factors using Cox proportional hazards regression analysis. We found that the survival time in high-risk patients was significantly shorter than in low-risk patients in both training and testing sets after Kaplan-Meier analysis. The AUROC value was 0.67 when predicting the survival time in testing set, which indicates a relatively high specificity and sensitivity. The results suggest diagnostic and therapeutic applications of our five-gene model for ovarian serous cystadenocarcinoma.