The Fake News Detection model employs logistic regression to discern between genuine and false information within textual data. It utilizes a range of linguistic and structural features from the news content to train the model. This includes analyzing word frequencies, topic modeling, and linguistic patterns to identify markers of deceptive or misleading content. The model aims to offer a reliable and automated system for filtering out fabricated news articles, assisting in maintaining the authenticity of news sources and minimizing the spread of misinformation.