for a completelly different kind of solution you can try using a neural-network package.

First you would need to generate some sample data, feeding some randomly distributed values into your "blackbox" and getting the output.

Then use the obtained set of input/outputs to train the neural-network and once the error goes below your acceptable limit, you could use it to replace the original blackbox.