Genetic Programming is a machine learning technique which has shown great promise for "automatically" solving problems in many disciplines. It attempts to mimic biological evolution to find solutions to complex problems. I will give an overview of genetic programming and show the results of applying this analysis method to a rare decay search. Using data from FOCUS at Fermilab, we have performed a search for doubly Cabibbo suppressed decays of the charmed hadrons Lambda_c and D_s. This is the first application of Genetic Programming to elementary particle physics data and the first limits on these decays. Comparisons with and increases in sensitivity over traditional analysis methods will also be presented.