DDoS Attаcks Distributed (DDoS) have an impact not only on availability but also on the network security of the Internet services and networks. The main purpose of these assaults is to generate an enormous traffic that the system must process to the point of it becoming inaccessible and unresponsive to authorized users. With the epitome of DDoS processes, there are increasing frequency and sophistication of the attacks, so their detection and prevention is imperative. Machine learning algorithms are the new force that brings machine learning techniques into the spotlight as a popular approach to solve this problem. It is a study that involves machine learning algorithms for estimation, identification, and prediction of DDoS attacks. Specifically, they can analyze and detect issues through data analytics and pattern recognition which are more effective and efficient than traditional rule-based approach.