This research explores the intricate relationship between fast-food consumption and obesity rates, employing a robust statistical model centered around multiple linear regression. The study incorporates key independent variables, including fast-food consumption, socio-economic factors, and lifestyle habits, to comprehensively analyze their impact on the dependent variable—obesity rates. Control variables encompass demographic and geographical factors, ensuring a nuanced examination of this complex association. Hypotheses testing reveals whether increased fast-food consumption correlates positively with higher obesity rates. Statistical analyses, such as correlation assessments, provide quantitative insights into the strength and direction of these relationships. The model's effectiveness is bolstered by random and stratified sampling, ensuring diverse representation across populations. Ethical considerations guide the research process, emphasizing informed consent, participant confidentiality, and responsible data handling. Interpretation of results involves assessing effect sizes and confidence intervals, fortifying the reliability and significance of the findings. Beyond statistical outcomes, this research offers actionable insights for policymakers and public health officials. Recommendations may span interventions addressing fast-food accessibility, public health campaigns, or educational initiatives targeting socio-economic factors and lifestyle habits contributing to obesity.