In recent years, the need and demand for the construction and utilization of light rail transit have been on the rise in Korea. As light rail transit construction projects have typically been promoted as Build–Transfer–Lease (BTL) projects, the private companies involved need to perform economic feasibility analysis by estimating life cycle cost (LCC) quickly and accurately. The success of a project greatly depends on the accurate analysis of the initial investment cost from the stages of design through construction, operating cost for the stages of operation and maintenance, and profits from operation. While such an LCC analysis requires a variety of experience with construction projects, a significant base of performance data and related expertise, Korean companies have no experience in the field of light rail transit construction, and the operating data is meager. With a lack of experience and data, the parties involved with light rail transit construction projects have come up with diverse costs estimates based on highly inaccurate data. Accordingly, it is urgent that there is a method to support the parties involved with light rail transit projects, particularly the private companies taking responsibility for investment in and operation of the light rail transit. This research aims to estimate the approximate construction cost of light rail transit structures (e.g. bridge, tunnel, etc.) and to develop an economic feasibility analysis system for light rail transit structures taking LCC into account based on the already calculated cost in order to support a reasonable decision-making process in relation with light rail transit construction projects. To estimate construction cost, major factors that have a great influence on the construction cost of the structure were first selected, and then a database for each unit cost was built. Using the system, a user can automatically calculate the construction cost by selecting the structure type and the engineering technique. For the LCC analysis, research of the literature was conducted, and based on the research an LCC analysis procedure and model was determined. In addition, by reviewing the uncertainty factors and the cost classification system appropriate for the construction of a light rail transit structure, the LCC analysis algorithm was written. Using the algorithm, LCC analysis of a bridge for a light rail transit was conducted to verify the feasibility of the algorithm that can provide information used for major decision-making, based on which private companies can determine whether or not to participate in a light rail transit construction project. This research has its own significance, both as a system to estimate construction cost for a light rail transit project based on diverse information, and as a system to analyze economic feasibility for LCC prediction.