The Bayesian Information Criterion (BIC) is a widely used equation for selecting the optimal number of components in a Gaussian Mixture Model (GMM). The formula is given by: $BIC = -2\log(L) + k\log(n)$, where $L$ is the likelihood, $k$ is the number of components, and $n$ is the sample size.