Most farm management decisions are made under conditions of uncertainty. This uncertainty in agriculture arises from market forces, weather, disease, insect damage, and other factors which cannot be controlled or accurately predicted. However, many agricultural economic models used to study farm management problems are specified under assumed certainty. For example, conventional linear programming used extensively in farm planning analyses does not accurately accommodate uncertainty. Of course, assumed yields and prices can be changed in these models to see how the farm organization is affected by changes in these variables. But there is no measurement of the risk associated with each farm organization. As a result, the conventional linear programming solutions of farm organizations have often been rejected because the solutions may specify actions that lead to a higher degree of risk than many farm managers are willing to accept [Chen, Freund]. The objective of this paper is to develop a multiperiod linear programming model that can be used to evaluate farm management decisions under uncertainty.