Recently, particularly following the COVID-19 pandemic and the beginning of people’s re- liance on Internet applications primarily to facilitate their lives, from requesting household needs online to medical consultations. It has been observed that fraud cases have increased due to people’s ignorance of these technologies, including (SMS) messaging applications, as banks and government agencies regard them as their official platforms for sending important messages to users. This platform also drew the attention of marketers because of its simplicity of use and low cost, which allowed them to send many messages, which became a nuisance and a waste of time. This study aims to create an application that can restore confidence and tranquility to (SMS) messages by comparing between types of supervised machine learning in an attempt to reach the highest possible rate of accuracy. The logistic regression model showed the highest accuracy in categorizing (SMS) messages with an accuracy rate of 88.33%. Developed a web- page where consumers can check out the message.