A credit-sensitive note (CSN) is a corporate coupon-bearing bond whose floating coupon rates link to the credit rating of the corporation. Acharya, Das and Sundaram proposed a model to price them, but their lattice algorithm runs in exponential time. Further, the Acharya–Das–Sundaram (ADS) model uses a constant credit rating transition matrix, which is rarely the case in reality. This paper incorporates a stochastic credit rating transition matrix into the ADS model and implements a simulation-based pricing method. When applied to CSN pricing, our approach is more efficient than the lattice method. It also shows that the stochasticity of the credit rating transition matrix has an impact on the prices, particularly for lower-rated classes.