To each second order random vector process there coresponds a reproducing kernel Hilbert space H(K), whose kernel is the covariance function K of the process. In the paper we propose a method to construct the scalar product of H(K) and the isometric transformation from H(K) to the Hilbert space of second order random variables generated by the process itself. Examples and statistical applications to extrapolation and regression problems are considered.