The outcomes of prairie reconstructions are subject to both unpredictability and complexity. Prairie, tallgrass, and mixed grass reconstruction is defined as the planting of a native herbaceous seed mixture composed of multiple prairie species (10 or more) in an area where the land has been heavily cultivated or anthropogenically disturbed. Because of the unpredictability and complexity inherent in reconstructions, some outcomes end up being failures dominated by exotic species. We propose that these failures follow a fat-tailed distribution as found in other complex systems. Fat-tailed distributions follow the Pareto principle, where 80% of the time reconstructions work as expected but 20% of the time they are surprising and far from the typical response. Therefore, we suggest managers be informed that reconstruction failures follow fat-tailed distributions as opposed to assuming reconstructions are simple and predictable with few failures. Once managers realize failures are inherent in reconstructions, resources can be allocated to more effective methods of dealing with failures rather than working to perfect the predictability of reconstructions. We suggest implementing adaptive management, especially where unpredictability is high, as a way to learn from failures. Combining learning from adaptive management with a reconstruction design process, in which goals and constraints are iteratively adjusted, can be a way to deal with failures and develop better outcomes.