Data preparation for Regression Model
Usually you can only predict with the variables you have trained on. But in a case like this, I would suggest you check the Multicollinearity of these missing variables with the ones you will have. May be they are already highly correlated with the features you already have. In that case, you can just model using the available features. 

If that is not the case and the missing variable looks like a significant variable in your regression, then you might need to pick some other variables which can help you indirectly derive the missing features. For example may be category helps you derive the rating with some accuracy.