Wildfire is an integral part of many ecosystems, and wildland fires also have the potential for costly impacts to human health and safety, and damage to structures and natural resources. Public land managers use various strategies for managing landscape conditions that can affect wildfire, broadly: fuel treatment (and other pre-fire risk mitigation), fire suppression, and post-fire landscape rehabilitation. However, with any of these strategies there is considerable uncertainty in the outcomes that managers can obtain, and thus on the societal costs and benefits associated with wildland fire management. Managers address that uncertainty by using available information to inform their strategy choices. The value of information (VOI) to the land manager is defined as the expected gains from improved wildland fire management outcomes that result from using the information. This paper discusses estimating the value of information using two approaches: a microeconomic theoretical approach, and the Bayesian decision-tree approach frequently used in the VOI literature. These approaches could be used for valuing specific pieces of information (with absolute values), and for prioritizing (with relative values) which areas to focus on for future research.