This article discusses the concept of identifiability in simple probability calculus. Emphasis is given to Bayesian solutions. In particular, we compare Bayes and maximum likelihood estimators. We advocate adoption of informative prior probabilities for the Bayesian operation in place of diffuse or reference priors. We also discuss the concept of identifying functions.