**Abstract**

Some strategic business problems cannot be expressed in analytical forms and, in most cases, are difficult to define in a deterministic manner. This chapter explores the use of probabilistic modelling using Monte Carlo methods in the modelling of decision problems. The focus is on using Monte Carlo simulation to provide a quantitative assessment of uncertainties and key risk drivers in business decisions. Using an example based on hypothetical data, we illustrate decision problems where uncertainties make simulation modelling useful to obtain decision insights and explore alternative choices. We will explore how to propagate uncertainty in input decision variables to get a probability distribution of the output(s) of interest.

**Keywords:** Monte Carlo methods, probability distributions, decision variable, probabilistic and stochastic modelling, decision analytics
