Contract farming is a growing practice in developing countries and first-world economies alike. It generates necessary guarantees to sustain the continued operations of vulnerable farmers while enabling the manufacturers to manage the aggregate supply and price risk. We consider a single manufacturer who owns several manufacturing plants, each with a random demand for the crop. The manufacturer selects a set of farmers to offer a menu of contracts, which is exogenously specified or endogenously determined. Each “selected” farmer chooses a contract from this menu in advance of the growing season. After the growing season, under known demands and supplies, the manufacturer minimizes the distribution costs from the selected farmers to the production facilities. We formulate this problem as a Stackelberg game with asymmetric information, where the manufacturer is the leader and the farmers are the followers. The manufacturer’s problem is a two-stage stochastic planning program for which we develop two solution approaches. We have applied our model to problem instances anchored on data from a large manufacturer of potato chips contracting with thousands of small farmers in India. We report on the performance of the solution methods compared with a lower bound based on the Lagrangean dual of the problem and show that the optimality gap is below 1%, for problem instances with 1,000 potential farmers. We also show how our model can be used to gain various managerial insights. As an example, when constructing the contract menu endogenously, often a small number of contract options suffices, depending on the degree of heterogeneity among the farmer pool. Thus, relatively simple menus often suffice.The online appendices are available at https://doi.org/10.1287/msom.2018.0735 .This paper has been accepted for the Manufacturing & Service Operations Management Special Issue on Value Chain Innovations in Developing Economies.