Frequent pattern mining has always been a topic of curiosity among the section of researchers and practitioners having a concern with data mining. It has proved its acceptance as a key complication in the field of data mining. The practice relates to the finding of itemsets that frequently appear in plenty of data under consideration. It is a kind of finding correlations and relationships between items involved in the data set. One may be interested in finding the frequent itemsets over the sliding window or in the complete data stream. In this research paper, the objective is to find all the itemsets that satisfy the minsup threshold. These itemsets are referred as frequent itemsets. Often the computational requirements for exploring the frequent itemsets are too expensive. The research paper elaborates the working of FP-Growth tree and formation of conditional FP-Tree via an example.