Crop production in the tropics is subject to considerable climate variability caused by the El Niño-Southern Oscillation (ENSO) phenomenon. In Southeast Asia, El Niño causes comparatively dry conditions leading to substantial declines of crop yields with severe consequences for the welfare of local farm households. Using a modelling approach that combines regression analysis with linear programming and stochastic simulation, and integrates climatic and hydrologic modelling results, the objective of this paper is to assess the impact of El Niño on agricultural incomes of smallholder farmers in Central Sulawesi, Indonesia, and to identify suitable crop management strategies to mitigate the income depressions. The results contribute to the formulation of enhanced development policies and provide guidance for future research activities. Based on resource endowment and location within the mountainous research area, we identify five farm classes by cluster analysis. Our linear programming model maximizes their cash balance at the end of the period most severely affected by El Niño. Main activities are the cultivation of rice, maize, and cocoa, for which external Cobb-Douglas production functions are estimated that include water supply as an input factor; they generate output according to level of production intensity as well as predicted weather patterns. Stochastic simulation is used to account for variations in crop yields due to factors not captured by the production functions. Iterative model runs produce probability distributions of the model outcomes for each household class, whereby the downside risk of failing to achieve a specified minimum level of income is particularly insightful. The results illustrate that drought-related crop management recommendations must be tailored to farm households according to their location, farming system, and resource endowment.