©2019 A.W. Heath et al. Uncertainty analysis is an important step in determining the reliability of a model. Models which are used to determine policies or guide decisions must be reliable to ensure sound choices are made. The Limits to Growth model by Donella Meadows and colleagues was one of the first computer models to investigate global issues of population growth and resource constraints. The model received much attention and criticism, sometimes being accused of being too sensitive to variations in input parameters. This paper studies the model's sensitivity to input error through an uncertainty analysis, and examines if this sort of analysis could have affected the debate surrounding the model's reliability and usefulness. Results showed that given the data used to calibrate the model, the output was susceptible to large variations, with the population variable returning a normalised standard deviation of 0.43. However, despite input error, the trends of the variables remain predictable.