Stem cells are unique in their ability to differentiate into diverse phenotypes capable of displaying radically different, yet stable, gene expression profiles. Understanding this multistable behavior is key to rationally influencing stem cell differentiation for both research and therapeutic purposes. To this end, mathematical paradigms have been adopted to simulate and explain the dynamics of complex gene networks. In this chapter, we introduce strategies for building deterministic and stochastic mathematical models of gene expression and demonstrate how analysis of these models can benefit our understanding of complex observed behaviors. Developing a mathematical understanding of biological processes is of utmost importance in understanding and controlling stem cell behavior.