Road crashes have become a common cause of deaths and injuries worldwide. The phenomenon is severe especially in the developing nations. The resulting mortality and morbidity due to road traffic crashes occurs mostly to the vulnerable road users such as motorized two-wheelers and non-motorized transport users. To address the burning issue, use of scientific methods for data collection, analysis and prediction modeling is highly recommended. The previous methods make use of the inference and the statistical models for the crashes in certain categories. However, the Ensemble and Machine Learning algorithm involves the correlations among the independent features and will not be used for casual reasoning. This research focuses on the analysis and prediction of road crashes using machine learning algorithms, particularly in the context of Jaipur city. It emphasizes the importance of scientific methods for data collection, analysis, and prediction modeling to address the severity of road traffic crashes. The research aims to build prediction models based on classification techniques, comparing the performance of various algorithms, and providing details of the contributing features.