How to make predictions based on correlations?
The correlation coefficient will tell you, how much predictive power the individual attributes posess with respect to profit in a linear sense.
Easier: The correlation coefficient tells you how line-like your data is.
( There might still be a very predictive arc like structure in your data which the correlation coefficient can't capture )   

So you can either calculate a regression line for profit with the attribute having the highest correlation coefficient, or you can calculate a hyperplane for all three attributes to get the desired prediction. Regression lines and hyperplanes are usually calculated by least-squares fitting.

But beware to overestimate predictive power, because it is extrapolation what you do. New data might behave different than old data which makes extrapolation potentially less exact the further you are away from known data.