Association rule mining is a process of discovering interesting and unexpected rules form very large databases. Discovery of association rules at primitive-level is called single-level association rules or primitive-level association rules. However, mining association rules at multi-level may lead to the discovery of more specific and useful knowledge from dataset. Mining of Multi-Level Association Rules (MLARs) are not useful until it can be used to improve decision making process. The main hurdle in this process is the number of rules grows exponentially with the number of items.