The uncertain nature and importance of the soybean market for Brazils economy are driving forces for improvement in the planning process of soybeans supply chain. This thesis presents a new stochastic programming mathematical model to assist in tactical planning of the soybean logistics chain. The model was conceived as a tool to assist the decision making of any trader involved in this highly complex market. The main spatial and temporal components of the soybean industry are addressed in the model. The objective function of the model maximizes the profit achieved based on the difference between the revenue from the sale of grain, meal and oil and the costs of transportation, processing, storage and the sale of grain, meal and oil. The model is intended to be applied for decisions related to tactical planning within a time horizon of one year. Aspects related to transport and purchase of soybeans contracts are incorporated in the model. The stochastic programming model is linear of two-stage with fixed resource structure. The model was applied to a real example with 21 points of origin, 11 silos, 6 processing plants, 5 points of the internal market, 6 ports and 225 arcs of transport, considering 243 scenarios, derived from the combination of four sources of uncertainty: purchase price and sale price of soybeans, foreign demand of soybeans and crop failure.