Ovarian cancer remains a leading cause of gynecological cancer-related mortality, primarily due to late-stage diagnosis. Effective pre-operative differentiation between benign and malignant ovarian masses is crucial for improving patient outcomes. This meta-analysis evaluates the diagnostic performance of carbohydrate antigen 125 (CA125), human epididymis protein 4 (HE4), the Risk of Malignancy Index (RMI), and the Risk of Ovarian Malignancy Algorithm (ROMA) by assessing their sensitivity, specificity, and overall accuracy. A systematic review of studies published between 2000 and 2024 identified 12 eligible studies with sample sizes ranging from 84 to 456 participants. Statistical analyses, including bivariate modeling and summary receiver operating characteristic curves, were performed. CA125 demonstrated the highest sensitivity (0.82) but had a high false-positive rate (0.357), limiting its specificity. HE4 exhibited higher specificity (0.171) and an improved diagnostic odds ratio (DOR = 17.00) compared to CA125. The ROMA and RMI showed comparable performance, with the ROMA achieving the highest area under the curve (AUC = 0.8619), followed by HE4 (AUC = 0.8586) and RMI (AUC = 0.8508), while CA125 had the lowest AUC (0.8128), indicating lower standalone diagnostic reliability. The findings suggest that HE4, ROMA, and RMI outperform CA125 in terms of specificity and overall diagnostic accuracy, with HE4 and ROMA particularly demonstrating superior specificity. These results support a multimodal diagnostic approach that integrates multiple biomarkers and risk indices to enhance pre-operative ovarian cancer detection and optimize patient management.