The purpose of this work is to present a new methodology and the associated computational tools developed within the U.S. Department of Energy Fuel Cycle Options Campaign to quantify the economic performance of complex nuclear fuel cycles. The levelized electricity cost at the busbar is generally chosen to quantify and compare the economic performance of different base load–generating technologies, including nuclear; the levelized electricity cost is the cost that renders the risk-adjusted discounted net present value of the investment cash flow equal to zero. The work presented here is focused on the calculation of the levelized cost of electricity of fuel cycles at mass balance equilibrium, which is termed levelized cost of electricity at equilibrium (LCAE). To alleviate the computational issues associated with the calculation of the LCAE for complex fuel cycles, a novel approach has been developed. This approach has been termed the island approach because of its logical structure, in which a generic complex fuel cycle is subdivided into subsets of fuel cycle facilities called islands, each containing one and only one type of reactor or blanket and an arbitrary number of fuel cycle facilities. A nuclear economic software tool, NE-COST, written in the commercial programming software MATLAB®, has been developed to calculate the LCAE of complex fuel cycles with the island computational approach. NE-COST has also been developed with the capability to handle uncertainty: the input parameters (both unit costs and fuel cycle characteristics) can have uncertainty distributions associated with them, and the output can be computed in terms of probability density functions of the LCAE. In this paper, NE-COST will be used to quantify, as examples, the economic performance of (a) once-through systems of current light water reactors (LWRs), (b) continuous plutonium recycling in fast reactors (FRs) with drivers and blankets, and (c) recycling of plutonium bred in FRs into LWRs. For each fuel cycle, the contributions to the total LCAE of the main cost components will be identified.