In today's era, there has been a surge in the risk of pneumonia attributed to modern lifestyles emerging as a prevalent concern. Various factors contribute to the development of this disease, including bacteria, viruses, fungi, inhalation into the lungs of food, liquids, or other substances, environmental factors such as the exposure to certain environmental factors such as smoke, pollutants, or chemicals, immune system weakness, age, malnutrition, smoking chronic health conditions including conditions such as chronic obstructive pulmonary disease, asthma, diabetes, heart disease, or kidney disease. Artificial intelligence now plays a crucial role in assisting medical professionals in diagnosing such severe conditions which can result in chronic effects such as long-term lung damage or worsen existing chronic lung conditions. This study aims to analyze patients' health metrics to determine if they are affected by pneumonia, utilizing machine learning techniques. Specifically, we have developed an algorithm that leverages Convolutional Neural Networks, while processing medical data to predict potential health issues associated with pneumonia.