Grappling with food scarcity and environmental concerns in today's globalized world, the efficient management of food resources is essential. This chapter comprehensively discusses the innovative synergy of machine learning (ML), Internet of Things (IoT), and blockchain technologies in managing the food waste problem. The chapter highlights the magnitude of the food waste problem, its origins, and its socio-economic and environmental consequences. The potential collaboration of these technologies with food waste management is elucidated. This chapter explores how ML algorithms can analyze vast datasets from the food supply chain, enabling predictive models for market demand forecasting, optimizing stocks, and lowering overproduction. Furthermore, adopting sensors through IoT for real-time monitoring of parameters crucial to food spoilage could ensure optimal storage conditions and automated timely signals for intervention in detrimental circumstances to mitigate spoilage. Additionally, after mentioning the principles of these technologies, the chapter illustrates the cooperation of these methods through case studies and their implementation in real-world problems. The chapter concludes by addressing the potential obstacles and opportunities of shifting paradigms. Several aspects, including privacy concerns, data security, and the digital divide, among the hurdles that necessitate considerable elaboration, are discussed. Finally, how these obstacles could be eliminated and the importance of collaborative efforts among stakeholders, including governments, businesses, and research institutions, is emphasized as a crucial factor for achieving adoption.