Lifecycle cost (LCC) analysis is a vital methodology for assessing the economic sustainability and long-term viability of aircraft systems across their entire operational lifespan. As highly complex engineering products, aircraft involve substantial initial acquisition costs, continuous operation and maintenance (O&M) expenditures, and strict safety and regulatory compliance requirements, all of which contribute significantly to overall lifecycle expenses. This study focuses on the comprehensive evaluation of aircraft lifecycle costs by integrating advanced digital twin (DT) technologies to enhance the accuracy and reliability of cost estimation and prediction. A structured mathematical modeling framework for LCC is developed, encompassing all major cost components, including acquisition, operational usage, scheduled and unscheduled maintenance, repair activities, and end-of-life disposal. The proposed framework enables systematic identification and quantification of key cost drivers that influence aircraft performance and economic outcomes. The results and discussion highlight how LCC analysis supports optimized maintenance planning, improves resource allocation, and facilitates informed decision-making for fleet management and system design. By leveraging real-time data, predictive analytics, and continuous system monitoring, DT-enabled LCC analysis reduces uncertainty associated with traditional cost estimation methods and enhances the ability to anticipate failures and maintenance needs. Furthermore, the integration of digital transformation trends within the aviation industry demonstrates the potential of DT technologies to improve operational efficiency, enhance safety performance, and extend asset life. Overall, the findings suggest that the application of digital twin-supported LCC analysis provides a powerful decision-support tool that strengthens economic efficiency, supports sustainable aircraft operations, and contributes to more resilient and cost-effective aviation systems.