CONTEXT: Confirmatory aldosterone suppression testing is widely utilized following positive screening for primary aldosteronism (PA), yet its incremental diagnostic value remains debated. While the 2025 Endocrine Society guideline proposes a probability-based approach, validated tools to translate this concept into clinical decision-making, particularly in Asian populations, are lacking. METHODS: Using a multicenter Common Data Model (CDM) across three tertiary hospitals (2002-2020), we retrospectively identified 307 patients who underwent SIT for suspected PA. SIT positivity was defined as post-infusion plasma aldosterone concentration (PAC) ≥10 ng/dL. We developed a conditional inference classification tree using screening-stage variables and compared its performance with conventional rigid screening criteria based on PAC and the aldosterone-to-renin ratio (ARR). RESULTS: Among 307 patients (mean age 51.2 years), 153 (49.8%) were SIT-positive. SIT-positive patients had higher PAC (median 32.9 vs. 12.7 ng/dL, p<0.001) and lower serum potassium levels (3.66 vs. 4.02 mmol/L, p<0.001). The decision tree identified a high-probability phenotype defined by PAC >25 ng/dL and PRA ≤0.55 ng/mL/h, with an SIT positivity rate of 96.4%. In patients with PAC 15.7-25.0 ng/dL, potassium ≤3.9 mmol/L further stratified SIT positivity to 68.8%, whereas patients with PAC ≤15.7 ng/dL had a low positivity rate. The tree-derived criteria outperformed conventional cut-offs, with an accuracy of 0.85, sensitivity of 0.83, and specificity of 0.86, and performance remained robust in internal validation and sensitivity analyses. CONCLUSION: A screening-stage decision tree provides clinically interpretable probabilities for SIT positivity, supporting risk-stratified confirmatory testing and selective omission in high-probability patients.