Sales Forecasting - Random Forest - Which features should I use for out of sample forecasting?
The question is poorly phrased, I've tried to edit it to the best of my abilities. However here are the problems you've stated, 


Some of the features which are being used now can't be used later because they might not be known. Will it affect the model? 
If they can be used, what type of algorithm can be chosen?  


The answer to the first problem, you have to check the accuracy first before making choosing any new features if the rest of your features give a good enough accuracy then there is no need to choose new features. 

The second problem, to predict those values of the features you are using now if they are discrete in nature try classification algorithms whichever fits the model best, else try something along the lines of regression if the input values are continuous. And then use these predicted values along with your existing model and check how the accuracy varies.