Adrenocortical carcinoma (ACC) is a rare and aggressive malignancy with poor prognosis. Surgery is the only curative option for ACC, but recurrence remains high. Effective systemic therapies are still lacking in ACC. Diagnosis currently relies on integrated hormonal, imaging, and histopathological assessments. However, distinguishing ACC from benign adrenocortical adenoma (ACA) remains challenging. To address this, we performed untargeted plasma metabolomics on patients with ACC and ACA, as well as on healthy controls, to identify differential metabolites and elucidate the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Notably, glycocholic acid emerged as a significantly upregulated metabolite in ACC with superior diagnostic accuracy. Furthermore, a metabolic model incorporating six plasma metabolites, including glycocholic acid, distinguished ACC from ACA and healthy controls with an area under the curve (AUC) of 0.9266. These findings demonstrate that plasma metabolomics might serve as a promising tool for the detection of ACC.