For Hölder continuous functions $f_i$, $i=0,\ldots ,d$, on a subshift of finite type and $Θ\subset \mathbb \R^d$ we consider a parametrized family of potentials $\{F_θ= f_0+\sum_{i=1}^d θ_i f_i : θ\in Θ\}$. We show that the maximum likelihood estimator of $θ$ for a family of Gibbs measures with potentials $F_θ$ is consistent and determine its asymptotic distribution under the associated shift-invariant distribution. A second part discusses applications; from confidence intervals through testing problems to connections to Bernoulli distributions and stationary Markov chains.