Early-warning for leakage in a recovery boiler can help the process operator to detect faults and take action when a dangerous situation is developing. By analysing the mass-balances on both the steam and combustion side of the boiler in a Bayesian network, the probability of leakage can be determined and used as an early-warning. The method is tested with real plant data combined with leakage simulations. The results show that it is possible to detect considerably smaller leakages using this method than using the type of simple steam-side mass-balance method that is in use today. Bayesian network is an efficient tool to combine information from measurement signals and calculations giving an early-warning system that is robust to signal faults