Abstract: Cellular processes are often viewed as systems of biochemical reactions. It has recently been observed that stochasticity plays an important role in many biological processes at the cellular level. Then, stochastic models are required for an accurate description of the system dynamics. Typically, biochemically reacting systems evolve on multiple time-scales, thus their mathematical models manifest stiffness. Stochastic models which, in addition, are stiff are computationally challenging, therefore the need for developing effective and accurate numerical methods for approximating their solution. We present several adaptive stepsize strategies for the numerical solution of stochastic models of biochemical systems. Numerical experiments on models of practical interest show the advantages of the adaptive strategies over the fixed-step methods.