When developing estimation tools that are highly intertwined with a physical experiment, engineers face challenges such as the need of specialized equipment, workforce, infrastructure, and unique driving conditions. Therefore, developing such tools may become time-consuming and expensive. Since it is not possible to have control over key driving conditions, the performance of the tool might be hinged to the handful of conditions under which it was tested. That rationale applies to road-load estimation, that relies on the coastdown experiment. For that reason, this paper proposes investigating how much can we leverage driving simulation for validating a real-time estimation tool such as a road-load estimator. The estimator uses recursive least square algorithm, and it is implemented with a complete vehicle model in real time using the MARCdrive driving simulator. The simulator allows for testing the tool under different driving conditions, i.e. wind, road friction, and grade. In addition, it allows the developers to analyze the impact of undesired driver actions during the coastdown test. The conclusions show how promising driving simulation is for the development of such tools, but also how it can be used to define the boundaries of driving conditions and driver actions in the physical experiment.