What @Michael Chernick said is correct from a statistician's viewpoint.
I'm a physicist, and in science, "model" can also mean a predictive description. You would say something like "if you set up the following situation, for example, place a small drop of ink in a glass of milk, then at time t you would expect the statistical distribution of ink molecules in space to be P[x, t]."
I suspect this meaning is becoming more ubiquitous. For instance, to be apropos, one might tell a potential client "if we target a certain population with such and such advertising, we would anticipate a voting increase of 4 ± 1 % for your candidate." This might be a purely empirical result, or it might be based on a predictive statistical model built on a theory combined with the results of statistical experiments.