evidence: In our latest research, we show that the pursuit of ever more complex models as tools to produce more accurate estimates and predictions may not work. Based on statistical theory and mathematical experiments, we ran hundreds of thousands of models with different configurations and measured how uncertain their estimations are. We discovered that more complex models tended to produce more uncertain estimates. This is because new parameters and mechanisms are added. A new parameter, say the effect of chewing gum on the spread of a disease, needs to be measured – and is therefore subject to measurement errors and uncertainty. Modellers may also use different equations to describe the same phenomenon mathematically.