The proliferation of fake social media accounts has become a pressing concern in today's digital landscape, with implications ranging from the dissemination of misinformation to identity theft and cyberbullying.Identifying and addressing the existence of counterfeit accounts is essential for safeguarding the integrity and security of online communities.In this study, we present a comprehensive approach to detecting fake social media accounts, leveraging advanced machine learning techniques and behavioral analysis. By conducting a thorough literature review and identifying the limitations of existing methodologies, we propose a novel framework aimed at enhancing the accuracy and efficiency of fake account detection. Our proposed system integrates feature extraction, machine learning classification, behavioral analysis, and contextual information to provide a robust solution for identifying fake accounts across various social media platforms. Through rigorous evaluation and validation, we demonstrate the effectiveness of our approach in enhancing trust and authenticity in online interactions.