Background: Fibromyalgia (FM) and osteoarthritis (OA) share common clinical properties and pathologic etiologies. In the current study we aim to assess the prevalence of overlapping FM in a population of knee OA patients and to evaluate the diagnostic performance of Western Ontario Macmaster (WOMAC) for FM in OA patients. Methods: In a single-center observational study we recruited a consecutive sample of 100 knee osteoarthritis. The OA patients were assessed for pain, stiffness and function using WOMAC and for possible FM diagnosis using ACR 2010 diagnostic criteria. In order to find independent predictors for fibromyalgia diagnosis, univariate and multivariate logistic regression analyses were utilized. The results regression analysis was used to build the final prediction model. Receiver-operating characteristic (ROC) curves and Youden's J index were used to identify the best cutoff values for predictor parameters of fibromyalgia. Results: In a population of 100 OA patients in this study, 41 had fibromyalgia based on ACR criteria. Age (mean of 55.43±8.94 vs. 51.4±8.59; P= 0.025), BMI (25.17±3.52 vs. 23.59 ±3.77; P= 0.03) and WOMAC score (46.19±14.10 vs. 35.69±11.19; P= <0.001) were significantly higher in patients with FM than patients without FM. Univariate analysis identified that the age, BMI and WOMAC score (Ps= 0.029, 0.041, and <0.001, respectively) are significantly associated with FM diagnosis. In multivariate analysis, WOMAC score (OR: 0.93 (95% CI 0.90–0.97), P< 0.001) was identified as independent predictors for diagnosis of FM. Using Receiving operator curve, the Area under the curve (AUC) of WOMAC score was 0.715 (95%CI: 0.614-0.817) and the optimum cutoff point for WOMAC score for diagnosis of FM was 43.5. Conclusion: It is concluded from this study that WOMAC scores > 43.5 are useful for suggesting FM as a secondary diagnosis in knee OA patients. Future studies are necessary to establish the results of the current study in a more general context, given the limited available evidence.