As an application of eigenvalues and eigenvectors we study Markov processes. We introduce the transition matrix of a Markov process and show that it has an eigenvalue equal to one. We show that a corresponding eigenvector whose entries add to one gives the steady state (or longterm behaviour) of the process. We give an example to illustrate these facts.