In this chapter, we introduce numerical methods for solving stochastic differential equations. Stochastic differential equations (SDEs) including the geometric Brownian motion are widely used in the natural sciences and engineering. In finance they are used to model movements of risky asset prices and interest rates. The solutions of SDEs are of a different character compared with the solutions of classical ordinary and partial differential equations in the sense that the solutions of SDEs are stochastic processes. Thus it is a nontrivial matter to measure the efficiency of a given algorithm for finding numerical solutions.