ABSTRACT Following the introduction of meta‐analytic methodology into anatomical research, anatomical meta‐analyses have increased substantially. However, extremely high statistical heterogeneity is frequently observed in these studies, while its implications remain insufficiently discussed within anatomical research. The present study investigated the current state and patterns of heterogeneity in anatomical meta‐analyses and explored the interpretive implications of heterogeneity in anatomical evidence synthesis. A PubMed search was performed on May 21, 2026, using the title‐based search strategy: ((meta‐analysis[Title]) OR (meta analysis[Title])) AND (anatomy[Title]). Anatomical meta‐analyses focused on human structural anatomy were included. Reported I 2 values were extracted and descriptively analyzed by overall distribution and anatomical category. A total of 132 studies were identified, of which 61 anatomical meta‐analyses with analyzable heterogeneity data were included. The mean reported I 2 value was 95.27% (range 41%–100%), with a median I 2 of 98.77%. Most studies demonstrated extreme heterogeneity, with 86.9% reporting I 2 values exceeding 90%. Category‐specific analysis demonstrated consistently elevated heterogeneity across anatomical systems, including skeletal structures (mean I 2 = 99%), peripheral nerves (mean I 2 = 95%), and vascular anatomy studies (mean I 2 = 94.56%). Despite this, pooled prevalence estimates were frequently reported with highly precise numerical values and narrow confidence intervals. Extreme statistical heterogeneity is highly prevalent across anatomical meta‐analyses and appears to represent a widespread characteristic of anatomical synthesis research rather than an isolated statistical phenomenon. Although such heterogeneity likely reflects genuine biological and methodological variability, pooled anatomical estimates should be interpreted with caution, particularly when highly precise numerical estimates are reported despite substantial interstudy inconsistency. These findings highlight the importance of transparent heterogeneity reporting and anatomically stratified approaches in future anatomical meta‐analyses.