A crucial requirement for service robots is to be able to move in dynamic environments shared with humans as well as interact with them. Navigation in such environments is a challenging task, as the environment is constantly changing, future states have to be predicted and planning and execution must be carried on-line. However, even in very complex situations, humans can easily find a path that avoid both dynamic agents and static obstacles. This paper proposes a technique to take advantage of the human movement in such populated environments, using a probabilistic approach for the leader selection, according to the robot's desired destination. By choosing a leader to be followed in dynamic environments, the robot can take advantage of the paths traveled by humans or other robots, effortlessly avoiding dynamic and static features as its leader does, relieving the robot from the burden of having to generate its own path. Both the leader selection and the leader following algorithms have been tested in a real environment, with a robotic wheelchair.