The increasing demand for sustainable agricultural practices and environmentally friendly pest management strategies has led to a surge in interest in biocontrol agents. These naturally occurring organisms, including bacteria, fungi, and viruses, offer eco-friendly alternatives to chemical pesticides by targeting and controlling pests and pathogens. This review chapter delves into the role of genome mining in the discovery and optimization of biocontrol agents, focusing on their diverse modes of action. Genome mining enables the identification of the genetic elements responsible for the biocontrol activities of these agents, uncovering novel genes, biosynthetic pathways, and mechanisms that contribute to their effectiveness. We explored various genomic and bioinformatic approaches used to analyze and interpret genomic data, providing insights into the molecular mechanisms of biocontrol efficacy. The chapter also highlights the integration of computational tools, such as machine learning and AI, to predict and enhance the action modes of biocontrol agents. Through a series of case studies, we illustrate the practical applications of these genomic techniques in improving biocontrol strategies and discuss the challenges and future prospects of genome mining in this field. This comprehensive overview underscores the potential of genome mining as a powerful tool for bioprospecting, ultimately advancing the development of more efficient and sustainable biocontrol solutions.