This research addresses the limitations inherent in current poultry weight prediction models. Existing models primarily rely on the age of chickens, resulting in inaccurate and insufficient predictions. As the industry evolves, precision in weight estimation becomes increasingly critical for stakeholders seeking to make informed decisions. Therefore, there is a growing demand for comprehensive models that incorporate additional variables beyond age. This study aims to enhance the accuracy of poultry weight predictions by employing machine learning techniques that utilize a diverse range of factors. By doing so, it seeks to provide more reliable estimates of chicken weight, thereby supporting better decision-making within the industry.