Integrated modeling stands at the forefront of understanding the multifaceted, simultaneous dynamics within systems, capturing the nuances of production and consumption. Its strength lies in its capacity to incorporate diverse operational and behavioral factors, offering a comprehensive lens to view complex interactions. In this talk, I demonstrate the application of integrated modeling to the realm of organic farming. By addressing both the operational aspects, such as price, inventory, and lead time, and the human-centered elements like attitude, perceived control, and societal norms, we offer a holistic insight into the push and pull factors influencing organic farming's adoption and sustainability. Using a synthesis of agent-based, discrete-event, system dynamics, machine learning, and optimization, our investigation provides a robust decision support system (DSS) that can be tailored to various agro-food scenarios. As organic farming becomes increasingly pivotal in the global quest for sustainable food production, our DSS serves as a valuable tool for stakeholders and policymakers aiming to harness its full potential.