Growing concerns over the impact of fossil fuels on climate change have driven efforts to find sources of energy with low emissions. In response, fluctuating renewable energy sources, such as solar and wind power, are growing to meet more of the electricity demand. However, maintaining reliable energy accessibility to the grid requires a stable, nonfluctuating source of power. Nuclear power plants (NPPs) provide nearly emissions-free, reliable energy to the grid (refer to “IPCC Fifth Assessment Report,” Intergovernmental Panel on Climate Change; https://www.ipcc.ch/report/ar5/). To best reduce reliance on fossil fuels while ensuring reliable energy generation and profitability, nuclear renewable hybrid energy systems (NRHESs) focus on tightly coupling renewable generation with a NPP by colocating the generation sources in an industrial park. The industrial park consists of at least the NPP, the renewable energy source, and some form of industrial process that consumes the energy not used by the grid. In this paper, we analyze the computational modeling approaches currently being pursued for NRHESs. We further investigate similarities between nuclear fuel cycle simulators (NFCSs) and NRHESs to determine how NRHES development can benefit from the development of NFCSs. This paper begins by reviewing past research on NRHESs to determine the necessary functionality of modeling software. After determining the necessary software capabilities for an NRHES model, we discuss the characteristics of a NFCS. The characteristics found common to both systems include desirability of a flexible modular design; open source; ability to be coupled to external pieces of software, including economic modeling, optimization methods, and sensitivity analysis; and results that are usable to technical and nontechnical people alike.