Money laundering has been in existence for a long time, but with recent developments in cryptocurrency technologies, using them as a new method of laundering criminal proceeds has become available to a wider audience of criminals due to mixer services. Bitcoin can be considered pseudonymous, and Mixer services attempt to obfuscate the money trail further by creating transactional chaos. Little is known about the exact functioning of these mixers and how criminals interact with these services. In this thesis, a literature study on existing anti- money laundering (AML) technologies and pattern analysis are applied. Unique to this research is the use of insider mixer administration data combined with the use of public blockchain data. The goal of this research is to gain insight into the degree with which mixer transactions can be identified as money laundering. This will increase the foundation for AML regulation and Law Enforcement procedures. The results show that a small share of the transactions can strongly be identified as money laundering, while for a large share of transactions the identification as money laundering is less strong. In addition, some unexpected phenomena such as reverse money laundering were identified.