Lung cancer is a type of cancer that starts in the lungs and cannot be prevented at the final stage but its risk can be reduced by treatments. Therefore, detection of lung cancer at the early stage is possible to reduce survival rate. The number of chain smokers is probably equal to the number of people affected by lung cancer. The lung cancer is predicted using the Logistic Regression. The study uses a logistic regression for categorical datasets. The model is obtained after parameter assessment, test the significance of each affecting attribute, and test the model. This is done to obtain prediction models and risk factors at the level of correlation of disease size. The results using logistics regression model for prediction of lung cancer patients based on symptoms, habits, and history of health diseases etc. to see the level of risk could have lung cancer. Some of the symptoms that affect a person with lung cancer are smoking, drinking alcohol, difficulty swallowing, coughing, chronic diseases, fatigue, and age.