PurposeThe purpose of this paper is to discuss and to help address the need for quantitative models to support and improve procurement in the context of humanitarian relief efforts.Design/methodology/approachThis research presents a two‐stage stochastic decision model with recourse for procurement in humanitarian relief supply chains, and compares its effectiveness on an illustrative example with respect to a standard solution approach.FindingsResults show the ability of the new model to capture and model both the procurement process and the uncertainty inherent in a disaster relief situation, in support of more efficient and effective procurement plans.Research limitations/implicationsThe research focus is on sudden onset disasters and it does not differentiate between local and international suppliers. A number of extensions of the base model could be implemented, however, so as to address the specific needs of a given organization and their procurement process.Practical implicationsDespite the prevalence of procurement expenditures in humanitarian efforts, procurement in humanitarian contexts is a topic that previously has only been discussed in a qualitative manner in the literature. This work provides practitioners with a new approach to quantitatively assess and improve their procurement decision processes.Originality/valueThis study adds to the existing literature by demonstrating the applicability and effectiveness of an analytic modeling technique based on uncertainty, such as stochastic programming with recourse, in the context of humanitarian relief procurement activities.