The first ABC-related ideas date back to the 1980s. Donald Rubin, when discussing the interpretation of Bayesian statements in 1984, described a hypothetical sampling mechanism that yields a sample from the posterior distribution. This scheme was more of a conceptual thought experiment to demonstrate what type of manipulations are done when inferring the posterior distributions of parameters. The description of the sampling mechanism coincides exactly with that of the ABC-rejection scheme, and this article can be considered to be the first to describe approximate Bayesian computation. However, a two-stage quincunx was constructed by Francis Galton in the late 1800s that can be seen as a physical implementation of an ABC-rejection scheme for a single unknown (parameter) and a single observation. Another prescient point was made by Rubin when he argued that in Bayesian inference, applied statisticians should not settle for analytically tractable models only, but instead consider computational methods that allow them to estimate the posterior distribution of interest. This way, a wider range of models can be considered. These arguments are particularly relevant in the context of ABC.