Empirical research involving projects is an important and common way to advance knowledge in the energy sector, and there are well-established approaches for qualitative analysis of single or few cases (1–10 cases) as well as quantitative analysis of large databases (from 50+ cases). However, the “middle-ground” of analysing 10–50 cases is an unknown territory, and very few approaches exist to deal with numbers of cases that lie in the range of 10–50. This paper shows how this “middle-ground” can be explored through Qualitative Comparative Analysis (QCA). This is a method that can be applied to energy infrastructure projects (such as construction, operations, and decommissioning of power plants) in order to study causal inference (e.g. factors associated with outcomes). This paper demonstrates the potential of QCA by showing its application on an energy infrastructure phenomenon with an intermediate number of cases, that of nuclear decommissioning projects. These projects are becoming increasingly important to society and have multibillion US dollar budgets. Moreover, their characteristics need to urgently be matched with their project performance in order to avoid even further cost overruns. The application of QCA to 24 European nuclear decommissioning projects shows that a combination of characteristics (such as a streamlined governance structure and the presence of a storage facility for radioactive material on site) might be contributing to lower cost overruns. This paper concludes by showing how QCA can be applied to other energy infrastructure phenomena with a similar intermediate number of cases.