In this letter, we propose a probabilistic approach to the generation of test patterns in the Chase Algorithm (CA) denoted as the Stochastic Chase Algorithm (SCA). We compare the performance of SCA with the regular CA for different Reed-Solomon codes. Simulation results show that the probabilistic nature of the SCA helps in providing a more efficient test pattern generation. SCA avoids the use of least reliable bits selection and reduces the number of candidate codewords up to 60% for the same decoding performance.