In this project, different state-of-the-art techniques from the field of Music Information Retrieval are applied to analyze Renaissance Music. Firstly, Symbolic Music analysis is being used to model the musical writing style of the several Renaissance-time composers in and around Flanders. Through this analysis new attributions to anonymous works from this time can be suggested, including the six unica in the Leuven Chansonnier. Secondly, this modelling technique is extended to raw audio analysis, such that performances of works can be analyzed in the same way. The way this technique can be used to model contemporary music is also explored. Lastly, a database of (visual) musical object detections, tied to the IDEM database, will be created. This database will be developed using the newest techniques from Computer Vision, Optical Music Recognition, and Active Learning. The analysis of Renaissance music in three distinct representations proves that this music is still highly relevant in the modern research setting of Music Information Retrieval.