The thesis involved the usage of the Backtracking Algorithm and Yolov5 to create a phishing and spam email detector. The researchers picked 55 respondents, ranging from Information Technology and Computer Science students, professors, professionals, normal Gmail users, and workers under the age of 60. After testing the system, the respondents answered a five-to ten-minute survey regarding the performance of the system. Based on the results of said survey, 64.2% of the respondents agreed that the system successfully detected phishing and spam emails as well as determining legitimate emails. Respondents’ comments include praising the scoring system as well as color-coding the email based on its severity so that the user may easily identify which was a phishing or spam email. There were also suggestions such as making the interface more colorful as well as having its results screen a refresh button to avoid going back to the dashboard and scanning once more. Given the results of the survey, the system was a near-perfect success, despite the minor errors and suggestions given. Future researchers would use this to expand the current application and improve its performance by adding a budget to its development as this application had no budget. Future researchers were also recommended to expand the system’s availability in operating systems, such as being able to be run in MacOS and(or) Linux, as well as being able to accept other types of online accounts such as Outlook.