[This was meant as a comment to Tim's answer, which I liked; but it's too long to be posted as a comment.]
There's a comment by Rasch along the lines of Tim's answer:
First a terminological remark. The "prediction" is suggestive of the statistician as a magician who can tell the future. Economists have an expression that is less pretentious: forecasting – not much more reliable than weather forecasting.
To speak seriously: you do not really predict anything. What you do, is to calculate the distribution of the variate in question, possibly offering its mean value or the like as a likely event – but only on the assumption that the model – or a characteristic feature of it – on which you based this forecasting, still holds, i.e. confronted with what eventually does happen you are faced with a test of this hypothesis and nothing else – you were not telling what the future would be!
on p. 268 of "Sufficiency, prediction and extreme models" by Lauritzen (Barndorff-Nielsen & al, eds: Conference on foundational questions in statistical inference, Aarhus 1973).
Personally I prefer to use "prediction" when a hypothesis assigns probability 1 (or 0) to some statement, and to use "forecast" otherwise. Because that hypothesis is then acting as a sort of physical theory with regard to that statement.
But also in that case the "prediction" is not guaranteed to be correct. Unit probabilities always come about from some simplification (which may be necessary for computational purposes) in our assumptions and beliefs.