In today’s rapidly evolving world of technology, the need to modernize legacy software systems has never been more pressing. Legacy systems are often outdated and difficult to maintain, posing challenges for organizations that need to innovate or scale. Modernizing these systems is a complex process, often hindered by Technical Debt (TD), which affects the costs of maintaining and adapting legacy code. Understanding which types of TD are most influential in the modernization process can help project teams make better-informed decisions, allocate resources efficiently, and minimize long-term risks. TD is multi-faceted, including architectural, code, design, and even documentation debt, all of which can impede modernization. We aim to analyze existing literature and case studies to understand which TD categories are prevalent and how they are managed. Much of the existing research on TD categorizes it into types such as code TD, design TD, architecture TD, and documentation TD. Previous studies have looked into how these types of debt accumulate over time. However, the role of TD in modernization projects has not been systematically reviewed. Current approaches to modernization largely focus on rewriting or re-architecting systems but fail to adequately address TD as a key factor in the decision-making process. The purpose of this master thesis is to explore the role of Technical Debt in the modernization of legacy systems. By conducting a systematic literature review (SLR) of real-world case studies, we will analyze how different types of Technical Debt contribute to the challenges in modernizing legacy systems.