Gibbs measures on subshifts of finite type can be described by their conditional densities given finitely many observations.  We use this property to develop optimal tests in the sense of Neyman-Pearson and to establish decisions based on the Maximum Likelihood method.  In particular, this involves extensions of the Ergodic Theorem and the Central Limit Theorem for stationary processes to the multivariate setting.