Expansion development of upgrading plants is an important decision to make for the oil sands industry. In this paper, we propose a multistage stochastic expansion development method to tackle uncertain synthetic crude oil (SCO) and CO2 tax prices. The linear decision rule based technique is applied to solve the proposed stochastic optimization model. Various analyses are conducted based on optimization results: (i) effects of the uncertainty set size, (ii) comparison of solutions for selected pessimistic, realistic, and optimistic scenarios, (iii) effects of different operating modes for an upgrading plant, and (iv) cost distribution. Results of this work demonstrate that the stochastic model provides a more flexible, economical, and robust solution compared to the deterministic solution. In addition, the CO2 tax price affects the optimal solution negligibly compared to the SCO price. Finally, expansion development of the studied upgrading plant is economically beneficial even at the current market state. (c) 2018 Elsevier Ltd. All rights reserved.