  A square matrix is called stochastic (or row-stochastic) if it is
non-negative and has each row sum equal to unity. Here, we constitute an
eigenvalue localization theorem for a stochastic matrix, by using its principal
submatrices. As an application, we provide a suitable bound for the
eigenvalues, other than unity, of the Randi\'c matrix of a connected graph.
