Assessing the present state of deteriorating structures is necessary for maintenance and retrofitting purposes. Bayesian updating using sequential Monte Carlo simulation (SMCS) is a powerful tool to estimate the state of a system using data from observation tainted with noise. To apply this method, brittle crack failure due to crack instability was investigated. Numerical simulations were done to determine the limit state exceeding probability at different times of the structure using ordinary Monte Carlo simulation. Assuming that crack length observations are available at specific times of the life of the structure the limit state exceeding probabilities are updated using SMCS. © 2011 Taylor & Francis Group, London.