This paper presents a simulation-based method automizing the application, performance evaluation and testing of predictive safety functions using the example of current AEB systems. The approach addresses the growing scenario complexity and the increasing performance requirements with several intended uses along the function development process. The approach overall aims at reducing specification, application and test costs by continuous simulation along the whole development process. The toolchain consists of three tools:​ Matlab, rateEFFECT and Optimus. Matlab serves as controller of the toolchain where the pre- and postprocessing takes place and the objective functions are defined. rateEFFECT is used as the underlying simulation environment. The driving simulation itself runs in this program and all kinds of load cases can be simulated. The optimization algorithms are provided by the tool Optimus due to its easy integration in the toolchain and above all its hybrid optimization techniques. Two simple ideas are presented to measure safety performance and customer acceptance. Furthermore, several optimization strategies and algorithms are analyzed:​ the metamodel-based-, the direct- and the hybrid-optimization.