is it possible to use the train result as another feature and retrain?
Yes but there are two issues:


Is it really useful? If the prediction is just added to the features on which it's based, it's unlikely to improve performance. However there are cases where this is useful, e.g. stacked learners.
You need to split the training set into two parts t1 and t2:


t1 is the regular training set used to produce the first model
t2 is the data used to predict the new "feature" and train the second model with this new feature.



It would be a bad idea to use the same training set for the two models because the predictions used in the second model would be obtained on the training set, so they would be unrealistically good.