This thesis proposes a new method to cluster law texts based on referential relation of case laws. We extract Case laws (Case law is law that has been established by following decisions made by judges in earlier cases.) and their referential relation from law texts. Then case law similarity algorithm is applied to calculate case law’s similarity through referential relation and Case law clustering is carried out based on the Case law similarity algorithm. To the best of our knowledge, this is the first time to apply Simrank algorithm in the domain of Law and use it to carry out text clustering. Prototype and experiments show that our solution is feasible. We also publish an available similarity case law search system which based on www.austlii.org case law database.