Deep learning has emerged as the best way to infer knowledge from data with more meaning and accuracy. The applications of Deep Neural Networks in a variety of domains have made it an important area of research. Crime analysis is the study of crime char acteristics and their relationships. The huge volume of crime-related datasets and the various different types of crime and their different characteristics and the complex relationship between them make Deep Neural Networks an ideal choice for this domain. The knowledge gained from this analysis will enable law enforcement officers to process information rapidly and accurately. In the paper, we have proposed a crime framework for India keeping in mind the language and cultural differences across the country. We have proposed automatically creating keywords from the written complaints and tagging the cases using Natural Language Processing. We have also proposed an approach using Deep Neural Network to classify the crimes and match the crimes to offenders using the method of operation. We have also used Deep Neural Networks for prediction of crime rates and hotspots. © IJSTR 2019.