The crime rate has skyrocketed in the preceding several years. The occurrence of crime is a widespread societal issue that has a negative impact on both living conditions and economic development. As crime rates rise, police departments have a growing need for cutting- edge technology and fresh strategies to enhance crime analytics and strengthen public safety. The use of a decision tree (J48) in the context of law enforcement and intelligence analysis shows promise in mitigating this issue. Data mining is an AI-based technique for gaining insight from big data sets by uncovering previously unknown connections between variables. Decision tree (J48) is one such AI technique. Machine learning is a significant area of study because of its many potential applications. It's no secret that criminology is a prime area for data mining applications. In order to better understand crime, criminologists use a systematic approach called criminology. According to the reviewed literature, the decision tree (J48) algorithm is the most effective machine learning algorithm for prediction of crime data, hence it was chosen for the construction of the study's prototype model of crime prediction. According to the findings of the experiments, the J48 algorithm was able to forecast the unknown category of crime data with an accuracy of 94.25287%, which is good enough for the system to be depended on for the prediction of future crimes.