Analyzing obesity through a comprehensive examination of physical health parameters and eating patterns is of paramount importance in understanding and addressing this complex health issue. Physical health parameters, such as body mass index (BMI) and waist circumference, serve as crucial indicators of an individual's overall well-being and can help identify potential health risks associated with obesity. By examining these parameters, healthcare professionals can tailor interventions and treatments to the specific needs of individuals, promoting more effective and personalized healthcare strategies. Similarly, delving into eating patterns is essential for gaining insights into the dietary behaviors that contribute to obesity. Understanding the intricate relationship between nutritional choices, cultural influences, and socioeconomic factors enables the development of targeted interventions aimed at fostering healthier eating habits. This study offers an optimal bagging ensemble model-based approach for analyzing obesity using physical health parameters and eating pattern. This approach combines both physical health parameters and eating patterns to provide a reliable analysis on the multifactorial nature of obesity.