Market Basket Analysis is an important part of the analytical system in the retail organization to determine the placement of goods, designing sales promotion for different segments of customers to improve customer satisfaction and hence the profit of the supermarkets.MBA is well known activity of ARM ultimately used for business intelligent decisions. Mining frequent item sets and hence deduce rules to build classifiers with good accuracy is essential for efficient algorithm. The issues for a leading supermarket are addressed here using frequent item set mining. The project uses file as database. Here, the itemsets and transactions of items are kept in a matrix form representing rows as list of items and column as transactions. The frequent item sets are mined from database using the Apriori algorithm and then the association rules are generated. The project is beneficial for supermarket managers to determine the relationship between the items that are purchased by their customers. Keywords: Market Basket Analysis, Association Rule Mining, Apriori Algorithm