Regulations are being introduced by the European Commission and the United Nations Economic Commission for Europe (UNECE) to accelerate the introduction of automated driving systems (ADSs) onto the public road. One of the main challenges for both vehicle manufacturers and vehicle authorities is to validate that the ADS drives safely and responsibly in all situations and under all conditions that the system might encounter on the road, so that the vehicle can be safely deployed. The UNECE WP.29 Working Party on Automated/Autonomous and Connected Vehicles (GRVA) proposes a Safety Assessment Framework (SAF) that allows stakeholders to determine whether a Cooperative Connected AutomatedMobility (CCAM) system meets a set level of safety on the road. The framework considers a scenario-based approach, where tests are based on real-world scenarios taking into account the CCAM system’s Operational Design Domain (ODD) and requirements. The real-world scenarios that feed into the SAF are knowledge based and/or data driven, ranging from accident scenarios to everyday driving scenarios. This chapter will commence with a recap of the UNECE Safety Assessment Framework giving a clarification of the important concepts, terms and definitions. We will show how to operationalize the framework and use (data-driven) real-world scenarios for the safety validation of ADSs. A method is proposed to estimate residual risk when deploying an ADS onto the road; the method is demonstrated on a relatively straightforward example. The code for these simulations is made publicly available, and a link to the code is shared.