Random Forest application with 40+ Predictor Variables
The randomForest package supports various tasks using an existing randomForest object.

For instance, it offers the predict method which will perform prediction using a given trained forest and a given dataset. As an example, if you have a trained forest called mod and a dataset called my_data, predictions can be obtained by running predict(object=mod,newdata=my_data).

It's worth reading through the package documentation which gives good examples of using the functionality.

I would note that any new data you supply to a trained forest object should have the same encodings and transformations as the data used to train the forest with.