Successful implementation of major projects requires careful management of uncertainty and risk. Yet such uncertainty is rarely effectively calculated when analysing project costs and beneﬁts. This paper presents a Bayesian Network (BN) modelling framework to calculate the costs, beneﬁts, and return on investment of a project over a speciﬁed time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN framework calculates costs and beneﬁts based on multiple causal factors including the effects of individual risk factors, budget deﬁcits, and time value discounting, taking account of the parameter uncertainty of all continuous variables. The framework can serve as the basis for various project management assessments and is illustrated using a case study of an agricultural development project.