As the crimes rates against women is increase day by day, the new problems are faced by the law organisation. Due to which this cause more burdens on the crime against women resources. The law organisation is able to generate such increases or decreases in crime, so it is necessary to find out the most useful method to control and avoid crimes against women. The aim of this paper is to classify clustered crime against women based on occurrence frequency during different years by the process of Data mining. Data mining is used to analysis, investigate and discovery of patterns for occurrence of different crimes against women. We connected a hypothetical model in light of information mining strategies, for example, grouping and characterization to real crime dataset recorded by OGD. The k-means clustering, KNN algorithm, decision tree algorithm and prediction method for future purpose, is used for the classification and clustering of crimes