Agent-based simulation is increasingly used to study systems
in many areas of business and science. Using agentbased
simulation for prediction could be very valuable.
However, these models usually have many parameters
which are difficult to measure directly leading to uncertainty
as to the best values to use. It is very important to
consider the alternative feasible sets of parameter values,
otherwise the modeling results could be misleading. A
method is described to take account of this when making
predictions and was applied to an agent-based word of
mouth consumer model. The result was a wide prediction
range indicating the limitations of using such a model for
predictions. The method could also be applied in other
situations.