If left untreated, human papillomaviruses (hr-HPV) infection can lead to pre-cancerous lesions and invasive cervical carcinoma (ICC). This infection causes over 90% of all cervical cancer in the world.[1] Timely diagnosis in precancerous lesions followed by medical referral, timely diagnosis, safe treatment and follow-up will be able to prevent cervical cancer at a relatively low cost.[4] Early detection with Visual Inspection with Acetic Acid (VIA) is an acceptable, affordable, and safe alternative method in developing countries. This process is relatively cheap and quick since it doesnt need any expensive tools and the results are able to be seen with the naked eye. The results are still determined manually by colposcopy which means that theres still a possibility of a misdiagnosis. Integrating an artificial intelligence (AI) that specializes in image classification using Convolutional Neural Network (CNN) into screening processes could offer faster and more accurate results to improve early detection and outcomes. The built model successfully identifies relevant visual patterns in cervical images, providing reliable predictions in classifying positive VIA and negative VIA cervicals. The proposed image classification model is proven to be effective in automatically detecting abnormalities which may lead to cervical cancer. Which shows the great potential of applying artificial intelligence technology in assisting the medical screening process.