I'm not clear what you're asking here.
If just want to check how good your predictions are on an out-of-sample dataset, just take the coefficients b you got from your original model, then form the predicted outcome P = X*b where X is the out-of-sample data you wish to check. Then, compare P and Y where Y is the actual out of sample outcome. The residual Y-P should give you a sense of how well your model performs out of sample.
In general, though, if you have more data you should include it in the original regression.
