Objective: To investigate the application value of metabolomics technology in the screening of indications for bilateral adrenal venous sampling (AVS) and the diagnosis and treatment of primary aldosteronism (PA), and to provide clinical evidence for the precise diagnosis and treatment plan selection of PA. Methods: A total of 25 patients with suspected PA after preliminary clinical screening admitted to our hospital from October 2024 to June 2025 were selected as the experimental group. Additionally, 15 patients with essential hypertension and 10 healthy individuals during the same period, totaling 25 cases, were selected as the control group. General clinical data and laboratory test indicators of the two groups were collected. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was used to detect serum metabolomic indicators. Differential metabolites were screened, and their correlations with AVS test results and the diagnosis and treatment of PA were analyzed. Results: There were no statistically significant differences in general data such as gender, age, BMI, systolic blood pressure, and diastolic blood pressure between the experimental group and the control group (P > 0.05). Serum aldosterone (ALD) and aldosterone-to-renin ratio (ARR) in the experimental group were significantly higher than those in the control group, while serum potassium levels were significantly lower (P < 0.001). There were no statistically significant differences in serum sodium, creatinine, urea nitrogen, and cortisol (COR) levels between the two groups (all P > 0.05). A total of 128 serum metabolites were identified by UPLC-MS/MS. After OPLS-DA analysis and screening (VIP > 1 and P < 0.05), 32 differential metabolites were obtained, of which 19 were significantly upregulated and 13 were significantly downregulated in the experimental group. Among the 25 suspected PA patients in the experimental group, 20 were diagnosed with PA (PA group) after AVS. No cases of PA were found in the 25 control subjects after examination. The sensitivity and specificity of the combination of metabolomic differential indicators and ARR detection were significantly higher than those of single ARR detection. Conclusion: Metabolomics technology can screen for differential metabolites associated with PA. These differential metabolites can serve as potential biomarkers for screening AVS indications. Combined with traditional laboratory indicators, they can improve the diagnostic accuracy of PA, providing important support for the rational application of AVS and the precise diagnosis and treatment of PA.