The moment generating function (MGF) of a random variable is a powerful tool in probability theory, providing a succinct way to encode all moments of the distribution. By differentiating the MGF, one can derive the moments, and it also facilitates the use of techniques such as the Central Limit Theorem and helps in proving distributional convergence.