The article presents some ways to estimate the distribution of the maximum likelihood estimate. Maximum likelihood estimate is important in large sample theory and has useful properties like being close to the true value. The challenge is that these estimates are found using nonlinear equations. The article discusses a hypothesis that suggests the variance of the maximum likelihood estimate gets closer to a certain value as the sample size increases.