Background: Ginger, a root originating in Southeast Asia, has several therapeutic benefits to human health, including antioxidant activity. Currently, there are discussions regarding the hypoglycemic properties of dietary supplements derived from its phenolic compounds in the management of chronic diseases. Diabetes mellitus is a chronic and complex disease that requires continuous treatment, with glycemic control being decisive in the management of hyperglycemia. Aim: This systematic review and meta-analysis aimed to identify the effects of oral supplementation of ginger in the treatment of type 2 diabetes mellitus (T2DM) in patients undergoing randomized clinical trial studies. Methods: Across the PubMed, Scopus, and Web of Science databases, randomized controlled trials that examined the role of ginger in T2DM until January 2022 were systematically researched. The parameters used to assess T2DM treatment control were Fasting Blood Glucose (FBS) and glycated hemoglobin (HbA1c). Bias risk assessment of the studies was performed using the RoB 2.0 tool. Meta-analysis was performed considering data compatibility. Results: Five studies were included in the analysis. Capsules containing Zingiber officinale powder were supplemented twice a day. The dose ranged from 1.2 to 2g/day, and the intervention period ranged from 4 to 12 weeks. Meta-analysis results indicated no significant effect of ginger supplementation on FBS or HbA1c. However, individual studies reported mixed results, with two studies showing a significant reduction in FBS. This suggests that while ginger may have potential as an adjuvant therapy, its overall impact on glycemic control in T2DM is not statistically significant when results are pooled. Conclusion: Currently published articles are still limited, requiring further studies of high methodological quality to verify the effectiveness of ginger supplementation on T2DM parameters control. (c) 2024 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.