In this study, a stochastic model for strategic planning of the butyric acid-to-butanol supply chain network (Ba-to-Bu SCN) is developed to consider variations in the butanol (Bu) demand and butyric acid (Ba) supply derived from industrial/municipal waste. The proposed stochastic model can help determine where and how much Ba to process, Bu to produce, and Ba/Bu to transport to minimize the total cost of the Ba-to-Bu SCN design under Ba processing and Bu demand uncertainties. The features and capabilities of the stochastic model are validated and compared to those of the deterministic model by application of the future Ba-to-Bu SCN design for South Korea in 2030. The optimization results illustrate that the expected total cost of Ba-derived Bu by the stochastic model (US $4898.55 thousand per year) was at least 0.18% more economical that that of the deterministic model (US $4889.72 thousand per year). The goal of this study is to develop a decision making tool for a stochastic strategic problem to improve bio-economy caused by uncertainties. The proposed approach will help balance cost efficiency with stability in the uncertain future biorefinery infrastructure.