AbstractThis article proposes a Probabilistic Time‐driven Activity‐based costing model. Time consumption is represented using probabilistic variables and Monte Carlo simulation technique is used to forecast total cost. The simulation experiments provide data to estimate a confidence interval for the total cost of a cost object. Hence, simulation can easily address variations in time forecasts and provide a more realistic characterization of total cost. The definition of the number of resources (e.g., employees) as decision variables allows analyzing alternatives and answer “what‐if questions”. The proposal would be very useful for an operation manager in analyzing uncertain scenarios and providing information indicating under what conditions different cost estimates are feasible.