<p>China’s soybean imports have expanded rapidly, yet most accounts remain descriptive and do not quantify the relative importance of macro demand, prices, and policy. This study addresses that gap by estimating the elasticities of key drivers using quarterly data (2010–2023) and a multiple linear regression framework. Variables include GDP, international and domestic soybean prices, the USD/CNY exchange rate, soybean tariffs, and rapeseed-oil imports. To ensure credible inference, all monetary series are deflated and log-transformed; multicollinearity is diagnosed with VIF and mitigated via stepwise model selection. Results show three robust determinants of China’s soybean import volume: (i) GDP has the largest positive effect, indicating macro expansion is the primary force behind rising import demand; (ii) international soybean prices exert a significant negative impact, confirming strong cost-sensitivity; and (iii) tariff increases reduce imports, with effects smaller than GDP but statistically meaningful. Exchange rate movements, domestic prices, and rapeseed-oil imports are not consistently significant once collinearity is controlled. The contributions of this paper are threefold: First, manage demand cyclicality by aligning feed and crushing capacity planning with macro conditions. Second, reduce price exposure by deepening participation in international price discovery and hedging, alongside strategic reserves. Third, calibrate tariffs and diversify origins through long-term contracts and logistics redundancy to enhance supply resilience.</p>