Introduction: Lung carcinoma __ampersandsignndash; Pulmonary disorders causes cancer-related death all over the world and in which majority due to cigarette smoking. With an increase in awareness about smoking being the major cause, other significant factors that play a vital role in causing the disease is unclear. There is no proper information among the public regarding the other symptoms which leads to identifying lung cancer in a later stage where it becomes incurable. Aims: The proposed system helps in early diagnosis, effective treatment and helps in creating awareness about the danger of lung cancer in occasional or non-smokers too. This system is to predict Lung Cancer at an early stage and validate the results using a CT scan. Methodology: An application that obtains user symptoms as input and prompts the user to upload a CT scan report of the lungs will be an efficient solution for early detection. This will aid in the early prognosis of the disease and effective treatment can be given. This application uses MATLAB to achieve its goal. Results: Among the various methods analyzed, Naive Bayes achieved an accuracy of 95.24% which proves to be a better solution for detecting Lung Cancer Conclusion: Thus, the proposed system has all the necessary features to detect lung cancer at an early stage thereby reducing the mortality rate and creating awareness among the public, of other parameters that are responsible for causing cancer.