In recent years, the increasing interest of music theorists in algorithmic analysis as well as the growing amount of musical corpora lead to advances in the field of computational musicology.
I present two examples for the application of mathematical and probabilistic models to musical data. Focusing on notes in Western classical music, I introduce a probabilistic model for pitch-class distributions of musical pieces based on the topological structure of the Tonnetz. The model allows for a quantitative comparison between pieces as well as historical comparisons between different composers. Turning to distributions of chords in 19th-century piano compositions, I demonstrate that they can be modeled using power laws and compare several composers under this model. These examples serve to show how explicit modeling not only aids concrete research questions at hand but also exposes which aspects are not yet fully understood and need to be addressed in future research.