Machine learning approaches have been applied across a wide range of questions in phylogenetic inference, ranging from substitution model selection to tree inference and to downstream inferences of introgression and diversification. I will highlight some of these applications and the machine learning algorithms that have been used in the field. I’ll also discuss the challenges associated with applying machine learning to questions in phylogenetics. Finally, I’ll discuss potential solutions to some of these challenges and the path forward for the successful application of machine learning to accommodate the complexity and heterogeneity that complicates phylogenetic inference.