Legacy mainframe systems are increasingly seen as costly and inefficient for meeting modern digital demands. Migrating these systems to modern platforms offers enhanced scalability, flexibility, and cost savings. However, migration comes with complexities such as preserving critical business logic and data integrity. Organizations must meticulously plan, execute, and validate the migration process to minimize disruptions and ensure smooth operation. The essential steps in preparing for a successful legacy mainframe database and application migration include assessment and analysis of existing databases, identifying modernization targets based on business criticality, technical complexity, and alignment with strategic goals, defining measurable goals, balancing quick wins and long-term value, engaging stakeholders, and making a strong business case. Assessment and analysis involve evaluating the current setup, analyzing data structures and schema alignment, identifying dependencies, and assessing integration points. Identifying modernization targets requires prioritizing systems based on their impact on revenue, customer engagement, operational dependence, technical complexity, and alignment with strategic goals. Defining measurable goals involves setting short-term and long-term objectives, balancing quick wins and long-term value, and aligning the modernization strategy with organizational capabilities. Stakeholder engagement is crucial for gaining support and alignment from key organizational stakeholders. This can be achieved by communicating the strategic value of modernization, engaging stakeholders early and often, demonstrating quick wins and early successes, and highlighting employee impact and upskilling opportunities. Creating a strong business case involves presenting a detailed analysis of costs involved in maintaining legacy systems compared to the investment required for modernization, addressing potential risks associated with migration, examining use cases, assessing key performance metrics, ensuring data is ready for migration, and showing projected ROI over time.