This paper gives a short review of the development of genetic parameter estimation over the last 40 years. This shows the development of more statistically and computationally efficient methods that allow the fitting of more biologically appropriate models. Methods have evolved from direct methods based on covariances between relatives to methods based on individual animal models. Maximum-likelihood methods have a natural interpretation in terms of best linear unbiased predictors. Improvements in iterative schemes to give estimates are discussed. As an example, a recent estimation of genetic parameters for a British population of dairy cattle is discussed. The development makes a connection to relevant work by Bill Hill.