Lung cancer is a specific kind of malignancy that arises in the tissues of the lungs, specifically in the cells that comprise the lining of the respiratory passages. Smoking is well recognized as the primary etiological factor contributing to the development of lung cancer. The inhalation of secondhand smoke, as well as exposure to asbestos or radon inside one’s own residence, Being employed, and having a familial predisposition to the ailment are further factors. Factors contributing to the chance of developing lung cancer. In their lifetime, 1 in 16 men and 1 in 17 women were diagnosed with lung cancer. The variability in survival rates may be attributed to the extent of illness dissemination at the time of its identification. Early detection may have substantial benefits. The term “impact” refers to the effect or influence that something has on a particular situation. The dataset was collected from a website. The study used a global-based Particle swarm Optimization (PSO) algorithm for feature selection. With our approach, we want to improve the dataset’s statistical feature accuracy and predict lung cancer accurately based on the given data. Among the employed classifiers, the Support vector machine and Naive Bayes obtained maximum accuracy of 97% with 8 out of 16 features.