The complexity of modelling risk in farming systems is explained and the artistic nature of the task noted. A brief outline is presented of an appropriate conceptual framework, drawing attention to the merits of stochastic efficiency criteria for analysis of systems when risk preferences of individual farmers are unavailable. A distinction is drawn between planning problems with and without embedded risk. The merits of 'utility efficient' (UE) programming are explained. Extensions of programming models, including UE formulations, to embedded risk using discrete stochastic programming are reviewed. The paper concludes with a discussion of the importance of correctly understanding the way risk impacts upon the target farming system, and then of formulating a programming model appropriate to the case.