Genetic programming is known to provide good solutions for many problems like the evolution of network protocols and distributed algorithms. Then, it is most likely a hardwired module of a design framework where it assists the engineer in optimizing specific aspects in system development. In this paper we show how the utility of genetic programming can be increased remarkably by isolating it as a component and integrating it into the model-driven software development process. Our genetic programming framework produces XMI-encoded UML models that can easily be loaded into widely available modeling tools, which in turn offer code generation as well as additional analysis and test capabilities. We use the evolution of a distributed election algorithm as an example to illustrate how genetic programming can be combined with model-driven development.