 Using different values for the parameters in your model will lead to different likelihoods for the tree. The maximum likelihood estimate is the tree hypothesis along with the fitted parameters which maximizes this likelihood. Felsenstein (1981) gave the first computationally feasible algorithm for calculating likelihoods, and with modern computing power combined with the huge amounts of sequence data available, likelihood methods have become the most commonly used methods in phylogenetics.