There is a need for new approaches to effectively manage vehicle insurance claims due to the rising trend in claim severity and quantity. Machine learning (ML) is one approach that addresses this issue. Car insurance firms have started implementing ML to improve the inter- pretation and comprehension of their data for efficiency, hence enhancing their customer service through a better knowledge of their demands, This is done in an effort to better serve their. This study investigates how auto insurance providers incorporate machine learning into their companies. To forecast the occurrence of claims, we will employ ML techniques like support vector machines. In this paper, A car insurance claim dataset from Kaggle is used. The research was carried out using support vector machines (SVM) to develop the prediction model. The experimental results showed that the model obtained good results with an accuracy of 99.9% .