The construction, operation and maintenance of transportation infrastructure require energy and materials which impact the environment. Large infrastructure projects thus use resources intensively and leave a significant environmental footprint. To demonstrate and support the sustainability of such large-scale projects, life cycle assessment (LCA) has become a common tool to evaluate environmental impacts in all stages of infrastructure life cycle, from raw material production through end-of-life management. However, the various phases of the assessment are all associated with uncertainties. If decisions are made without consideration of these uncertainties, they might be misleading and suboptimal. In this paper, results are presentedwhere variations associated with different parameters and tools for life cycle assessment have been considered using probabilistic methods. A categorization of common uncertainties in LCA is also included. The most influential parameters can be identified with sensitivity analysis methods, since for LCA with a large number of parameters it may be unreasonable to incorporate all in a probabilistic simulation. For a limited amount of influential variables, Monte Carlo simulation has been used to assess the effects of uncertainties on the results.A bridge has been used as a case study to find important aspects in infrastructure LCA. The results indicate that if the most influential parameters are considered as random variables, it is possible to estimate the uncertainty and increase the validity of the life cycle assessment.