Nepal’s agriculture faces multiple challenges, including low productivity, fragmented landholdings, climate vulnerabilities, and inefficient resource utilization. These challenges not only hinder agricultural productivity but also threaten food security and the livelihoods of millions of smallholder farmers. Simulation modeling and artificial intelligence (AI) tools—such as crop models, Geographic Information Systems (GIS), remote sensing, machine learning, and digital platforms—offer transformative solutions to address these issues and modernize agriculture. This chapter presents an actionable roadmap for implementing these tools in Nepal, emphasizing scalable strategies and region-specific applications to address agricultural constraints. It focuses on optimizing resource use, enhancing yield forecasting, improving climate resilience, and empowering farmers through data-driven ICT-enabled agro-advisory services. It provides insights into financial and operational frameworks necessary for technology integration, with specific emphasis on provincial-level implementation and stakeholder capacity building. The roadmap highlights key requirements, including the development of robust data and computational infrastructures, capacity building for stakeholders, and the integration of crop modeling and digital tools into national agricultural policies. It also identifies barriers to scaling up those tools across diverse agroecological zones. The chapter underscores the need for fostering collaboration across public and private sectors to enhance productivity, sustainability, and resilience in agriculture. We hope that the insights and recommendations provided in this chapter serve as a guide for policymakers, researchers, extensionists, and leader farmers for transforming agriculture into productive, sustainable, and climate-resilient, ultimately improving food security and farmers livelihoods.