In recent years, technological innovations have resulted in manifold applications using rare earth elements (REEs), leading to a dramatic increase in demand for them. Because of their unique physicochemical properties, REEs are considered indispensable in modern industry. They are extensively used in new materials, energy conservation, environmental protection and IT devices as well as in military weapon systems. They have also significantly contributed to the miniaturisation of electronic components, such as, for example, cell phones and laptop computers. REEs are essential for green technologies such as wind turbines. They are widely applied in the automotive industry for catalysts, hybrid vehicle batteries, motors and generators, etc. (Hurst, 2010). Due to the similarity of the chemical characteristics of each individual REE, the production processes for REEs with high purity are very complex: the processing and separation can be technically challenging. Furthermore, the chemical extraction processes involved have generated severe environmental problems. Currently, the supply of REEs is concentrated in China. To reduce the dependence on China, many countries have started to search for alternative REE sources, which can be classified into “primary sources” and “secondary sources”. Many REE exploration projects outside China and REE recycling projects have been launched. However, the success of the development of these projects is impacted by various risks, such as political risks, technical risks, environmental risks and social risks. The main research aim of this thesis is to establish a model for the evaluation of REE projects and to provide a basis for investment decision making. In order to complete this task, an analysis of REE deposits and the supply chain for REEs is provided. As results, a data base of potential REEs project is compiled, while an overview of the supply chain for REEs and an analysis of risks across the supply chain are presented. In order to assess potential REE production projects, a new real options valuation (ROV) model using a multi-dimensional binomial lattice approach is developed. For the application of the new real options model, a range of risk parameters and the expected production output of REE products are estimated using the Monte Carlo simulation method. The application of the new real options model is presented for the evaluation of the Bayan Obo mine in China, the Kvanefjeld REE project in Greenland, and a REE recycling project from magnetic scrap.