Parallel computing demands pseudo-random number generators that maintain independence and reproducibility across multiple processing units. This chapter introduces an automated method for parallelizing PRNGs, with a focus on Linear Congruential Generators (LCGs) and DX generators. Essential properties such as scalability, long periods, and efficiency are analyzed. Traditional LCG parallelization approaches are evaluated, revealing inherent limitations. The proposed method systematically constructs independent parallel sequences while mitigating overlap issues, ensuring improved performance in high-performance computing environments.