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Email spam is one of the unsolved problems of the today's Internet, annoying individual users and bringing financial damage to companies. Among the approaches developed to stop spam emails, filtering is a popular and important one. Common uses for email filters include organizing incoming email and computer viruses and removal of spam. As spammers periodically find new ways to bypass spam filters and distribute spam messages, researchers need to stay on the forefront of this problem to help reduce the amount of spam messages. Currently spam emails occupy more than 70% of all email traffic. The negative effect spam has on companies is greatly related to financial aspects and the productivity of employees in the workplace. In this paper, we propose the new approach to classify spam emails using support vector machine. It found that the SVM outperformed than other classifiers.