Algebraic statistics is an exciting area of math that studies statistical models using algebraic geometry, commutative algebra, and combinatorics. In this talk I will introduce two classical objects in algebraic statistics: the maximum likelihood estimator (MLE) and maximum likelihood degree (ML degree). We will explore these objects with an example from phylogenetics: Brownian motion tree models. This exploration will include a generalization of the Cayley-Prufer theorem that arises in computing the ML degree of Brownian motion tree models.