The agricultural environment has seen a considerable transformation due to the relentless advancement of technology, which has brought newfound solutions to long-standing problems. This chapter examines how machine learning (ML) and artificial intelligence (AI) are revolutionizing pest and disease control in the agricultural sector. It is critical to integrate cutting-edge technologies into global agriculture as it faces unprecedented challenges in ensuring food security in the face of a rapidly changing climate. The conversation progresses through an analysis of cutting-edge models and algorithms that provide farmers with predictive analytics, empowering them to forecast and reduce any risks to crop health. Farmers can ensure maximum resource allocation, limit chemical usage, and minimize environmental impact by incorporating these technologies into precision agriculture systems. This chapter explores the many uses of AI and ML in agriculture, from precision farming methods to early disease and pest detection and diagnosis, hence promoting a paradigm shift in conventional agricultural practices. We discussed specific applications, such as image recognition for pest and disease diagnosis, predictive modelling for outbreak forecasting, and decision-making support systems for optimizing control strategies. Additionally, we address the challenges and limitations associated with AI adoption in agriculture, emphasizing the need for robust data infrastructure, ethical considerations, and farmer training for successful implementation. To help researchers, practitioners, and policymakers achieve sustainable and resilient agricultural systems, it provides a thorough grasp of how AI and ML can be used as effective tools. With an emphasis on the future of AI and ML in pest and disease control, this chapter concludes by presenting possible collaborations with cutting-edge technology.