In our daily life often we face some unforeseen problems. The way we tackle those problems is by thinking about similar or near similar situations we encountered in past and then applying the knowledge learned at those known problems to the current problem. This is also in short the way in which human experts solve unknown problems. In the world of artificial intelligence, there is a constant effort of mimicking human experts. In this context, case based reasoning is evolved as a ew methodology of automatic reasoning. By definition a case is a situation or problem in terms of natural language descriptions and answers to questions and associates with each situation a proper business action. Case-based reasoning (CBR), broadly construed, is the process of solving new problems based on the solutions of similar past problems. An auto mechanic who fixes an engine by recalling another car that exhibited similar symptoms is using case-based reasoning. A lawyer who advocates a particular outcome in a trial based on legal precedents or a judge who creates case law is using case-based reasoning. Currently case based reasoning is widely used in e-Commerce, Information retrieval, Designing, iagnosis and in many other fields. The present seminar will present a comprehensive discussion on the principles of case based reasoning and briefly introduce some of its popular applications in various fields