As a result of the appearance of different media platforms and the use of the internet helps in spreading the fake news in a rapid way. So, there is no restriction and limitation while posting this news in the platforms. Some people benefit from these platforms by spreading the fake news against individuals and organizations. That cause great harm as it may destroy people's reputation or affect business. So, the best solution is detecting the fake news with the help of the machine learning classifiers.The main goal and the objective of the project is to face the issue of the fake news. So, one of the greatest solution tools in detecting the phenomena of the fake or the false information is the machine learning. The classifier of the machine learning that I have used is the “logistic regression” in detecting the credibility of the news if it is true or false and this depends on the classifier is will trained due to the result of the collected data as the collected data is collected as training the machine learning algorithm as the main goal of the project that is achieved successfully in detecting the fake and real news. According to the implementation phase the accuracy of the trained logistic regression model is pretty good so in the machine learning the thing that distinguish the classifiers are the accuracy, the more accuracy is considered the better classifier that helps in detecting more fake news. Also, the evaluation and ensures of testing part is been used in two parts which is “white box testing and the black box testing” in order to check the performance and the efficiency of the project.