Objectives: There is no optimal preoperative model predicting complete primary cytoreduction in patients with advanced ovarian cancer. If complete cytoreduction is not achievable, neoadjuvant chemotherapy can be an alternative treatment option. Thus, we aimed to develop a model predicting complete cytoreduction in primary cytoreductive surgery (CRS) using clinicopathologic characteristics and 18F-FDG PET/CT-derived parameters in advanced ovarian cancer. Methods: We retrospectively identified patients with stage III-IV ovarian cancer who underwent primary CRS between June 2013 and February 2020 at Seoul National University Hospital and Samsung Medical Center for development of a prediction model and for its validation, respectively. Complete cytoreduction was defined as grossly no residual tumor after CRS. We divided abdominal cavity into three sections in 18F-FDG PET/CT images. The number of lesions in each section was counted and visual grading was conducted. Then, standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were estimated. We constructed various prediction models for complete cytoreduction by combination of clinicopathologic characteristics and 18F-FDG PET/CT-derived parameters. Predictive performance of each model was assessed based on area under the receiver operating characteristic curve (AUC). The model showing highest AUC was selected and its performance was evaluated for validation. Results: Prediction models for complete cytoreduction were designed with an independent development cohort (n=159). In the process of variable selection, MTV, TLG, and the number of lesions above the renal vein were selected among 18F-FDG PET/CT parameters with other clinical variables including serum CA-125 level by AUC basis. The highest predictive performance was achieved by combination of serum CA-125 level (<750 or ≧750 IU/ml), the number of lesions above the renal vein (<2 or ≧2) and MTV above the renal vein with AUC of 0.770. This three-parameter prediction model was finally selected for validation with another independent cohort (n=169). The model predicted complete cytoreduction with AUC of 0.777. Conclusion: We successfully developed and validated the 18F-FDG PET/CT-based predictive model for complete cytoreduction. This result may be helpful for gynecologic oncologists to choose primary CRS or neoadjvuant chemotherapy in patients with stage III-IV ovarian cancer in real-world clinical practice.