Cosmological parameter estimation is a critical part of modern cosmology, but it is computationally challenging. I will review how Monte Carlo Markov chain methods have been introduced to solve this problem. Furthermore, I will discuss how new algorithms can be used to achieve high performance through parallelization and point out why this is relevant for analyzing the increasingly complex datasets of current and future observations.