Background and Objectives: The escalating prevalence of gestational diabetes mellitus (GDM) and the limitations associated with utilizing body mass index (BMI) as a predictive measure underscore the imperative need for identifying an optimal early pregnancy predictor. Such a predictor not only mitigates the risk of GDM but also allows for timely implementation of interventions. Materials and Methods: This meta-analysis aimed to explore the association between visceral adipose tissue (VAT) depth and the risk of GDM. A thorough search of PubMed, Embase, and Web of Science databases was conducted up to 30 September 2023. The analysis employed a random-effects model to assess the relationship between VAT depth and the likelihood of GDM. Results: The inclusion criteria encompassed seven studies involving 1315 women, including 225 diagnosed with GDM. Significantly lower VAT depth was observed in the non-GDM group in comparison to the GDM group (Standardized Mean Difference [SMD]: 0.84; 95% Confidence Interval [CI]: 0.52-1.15; p < 0.001). Substantial statistical heterogeneity was noted among studies (I2 = 72.88%, p = 0.001). Through meticulous sensitivity and subgroup analyses, the source of heterogeneity was identified and thoroughly discussed. Subgroup analyses suggest that different GDM diagnostic criteria and VAT definitions all indicate higher VAT depth in GDM patients during early pregnancy. Conclusions: Our findings propose that, during the first trimester, GDM patients exhibit higher VAT depth compared to non-GDM women, highlighting VAT depth as a potential predictive factor for GDM in early pregnancy. This study contributes valuable evidence to the growing body of knowledge surrounding novel predictors for GDM, emphasizing the importance of early intervention strategies.