Traditional functional budgets are useful for planning under predictable business environments. However, due to increased competition, changes in technology, consumer attitudes, and economic factors affecting supply chains, accountants must understand the characteristics of risk and uncertainty. Additionally, businesses now have access to unprecedented amounts of data pertaining to customers, suppliers, marketing operations, and activities throughout the value chain. Consequently, accountants should be able to harness the computing power, data storage capacity, and availability of analytical tools to analyze and manipulate large data sets to succeed in a data science world. A statistical technique available to accountants to perform predictive and prescriptive analytics is Monte Carlo simulation. This chapter illustrates how to use Monte Carlo simulation in developing a probabilistic cash budget which facilitates better risk assessment, resource allocation, and decision making compared with the traditional deterministic approach. [For the complete volume, "Advances in Accounting Education: Teaching and Curriculum Innovations. Volume 28," see ED674684.]