Phylogenetic trees are crucial to many aspects of taxonomic and comparative biology. Many researchers have adopted Bayesian methods to estimate their phylogenetic trees. In this family of methods, a model of morphological evolution is assumed to have generated the data observed by the researcher. These models make a variety of assumptions about the evolution of morphological characters, and these assumptions are translated into mathematics as parameters. The incorporation of prior distributions further allows researchers to quantify their prior beliefs about the value any one parameter can take. How to translate biological knowledge into mathematical language is difficult, and can be confusing to many biologists. This review aims to help systematics researchers understand the biological meaning of common models and assumptions. Using examples from the insect fossil record, I will demonstrate empirically what assumptions mean in concrete terms, and discuss how researchers can use and understand Bayesian methods for phylogenetic estimation.