The data included means of entry (front door, window,etc.), day of the week, characteristics of the property (apartment, house), and geographic proximity to other breakins.Using nine known crime series of burglaries Series Finder recovered most of the crimes within these patterns and also identified nine additional crimes. The predicted result showed more than 80% accuracy. So the same concept we are applying here i.e. find unknown patterns from known data and facts [5]. It's the first mathematically principled approach to the automated learning of crime series