With the inception of Bitcoin in the year 2009 a revolution was kicked-off and blockchain technology gained more and more traction. First, it was limited to the financial sector only but in the recent years the immense potential of this technology was also recognized across other business sectors such as the supply chain industry. The technology evolved and now it is not only blockchain technology which is interesting for such applications but the much broader term of distributed ledger technologies (DLTs). Inherent characteristics of such technologies are for example to build trust among various parties which do not trust each other and it can bring transparency into applications in ways which are never seen before. Because of these characteristics DLTs are seen as a big opportunity for increasing the transparency and traceability in supply chain applications. Currently the development of DLTs is in a very fast evolving state and research on the intersection of DLTs and supply chain applications is in an early state. As there are many options to choose from and DLT designs bring various strengths and weaknesses to the specific use case, the process of selecting the right DLT design is very important for the overall success of the application. This part, specifically, is covered badly in current research articles, as the current research is still for the most part focused on blockchain technology only and often times no consideration was given to the selection process of an appropriate DLT design. The goal of this thesis is to fill this gap by covering DLTs beyond blockchain technology and to comprehensively cover the selection process of an appropriate DLT design for a supply chain application. The aim is to develop a quantitative evaluation model, which can be applied by organisations wanting to implement a DLT solution in their supply chain operations. The model will be developed based on a systematic literature review, the results of qualitative expert interviews and lastly by rating different DLT designs with the help of a quantitative survey conducted with domain experts. Limitations could arise through the fast evolving state of DLTs, and through the process of interviewing a only a limited amount of experts for the most important parts of this model.