  Genetic Algorithms are introduced as a search method for finding string vacua
with viable phenomenological properties. It is shown, by testing them against a
class of Free Fermionic models, that they are orders of magnitude more
efficient than a randomised search. As an example, three generation, exophobic,
Pati-Salam models with a top Yukawa occur once in every 10^{10} models, and yet
a Genetic Algorithm can find them after constructing only 10^5 examples. Such
non-deterministic search methods may be the only means to search for Standard
Model string vacua with detailed phenomenological requirements.
