Analyzing the United States/Brazil competition for market share of Chinese soybean imports requires a detailed, stochastic approach. Using data from 2013 to 2019, this thesis attempts to model and explain the change in market share for each producing country as different variables fluctuate or enter the equation. Using five origins in each country, the PNW, USG, Santos, Paranaguá, and the northern arc of ports in Brazil, various transportation routes from origin to port, congestion and quality metrics, and ocean freight, a least-cost optimized Monte Carlo simulation is performed using time-series forecasting distributions for monthly variables. A distribution of outcomes for changes in market share over the crop year demonstrates that Chinese importers favor U.S, soybeans from December to March and Brazil soybeans the alternate months. In the base case Brazil captures almost two-thirds of China’s soybean imports. Sensitivity analyses include trade disputes, quality discounts, improved infrastructure, and congestion costs.