Cramér's Theorem is a result in probability theory that provides a way to approximate the distribution of a sum of independent random variables. Specifically, it states that under certain conditions, the distribution of the normalized sum converges to a normal distribution as the number of variables increases. This is significant because it helps in understanding how random variables behave collectively. The theorem is named after the Swedish mathematician Harald Cramér, who contributed to the field of statistics and probability. Cramér's Theorem is often used in conjunction with the Central Limit Theorem, which also deals with the convergence of distributions.