The aim of this paper is to demonstrate the R package conting for the Bayesian analysis of complete and incomplete contingency tables using log-linear models. This package allows a user to identify interactions between categorical factors and to estimate closed population sizes using capture-recapture studies. The models are fitted using Markov chain Monte Carlo methods. In particular, implementation of the Metropolis-Hastings and reversible jump algorthims appropriate for log-linear models are employed. The conting packae is demonstrated on four real examples.