Rational matrices G(x) arise in many applications such as in vibration analysis of machines, buildings, and vehicles, in control theory and linear systems theory and as approximate solutions of other nonlinear eigenvalue problems. The spectral data (poles, zeros, eigenvalues, eigenvectors, minimal bases, and minimal indices) of G(x) play a vital role in many applications. In this talk, we propose the definition of Rosenbrock strong linearization of rational matrices: by a Rosenbrock strong linearization of a rational matrix G(x) we mean a matrix pencil L(x) preferably of smallest dimension that reveals the pole-zero structure of G(x). Then we construct a family of pencils (which we refer to as GFPRs) of G(x) and show that GFPRs are Rosenbrock strong linearizations of G(x). Moreover, we show that GFPRs of G(x) is a rich source of structure-preserving linearizations of G(x) and utilize these pencils to construct structure-preserving Rosenbrock strong linearizations of structured (symmetric, skew-symmetric, even and odd) rational matrices G(x). Finally, we describe the recovery of eigenvectors, minimal bases, and minimal indices of G(x) from those of the GFPRs.