Multiple fatigue cracks, causing transient fatigue fracture and resulting in great loss of life and property, are very commen in engineering structures. In order to predict the fatigue life of engineering alloys more accurately, the interaction and coalescence of adjacent cracks was investigated and the four stages of cracks growth were discussed in this paper. The SIF(stress intensity factor) value was found to growth rapidly in the ligament failure, and simulation method was used to find out the coalescence point. Then, the Paris’ law was chosen to discribe the crack growth process. Taking random factors like structure size, material properties, environment stress parameter into account, the probability physical of failure model of alloys can predict the failure life more accurate. Accordingly, the uncertain parameters of the Paris’ law were updated via Bayesian update method. The posterior distributions of uncertain parameters were obtained by the MCMC-Gibbs sampling. Finally, the probabilistic failure life models before and after coalescence were established by Monte Carlo simulation method. The probabilistic modeling method, which can greatly reduces the historical data or experimental data needed for the reliability evaluation of small sample products, can also be applied to other aspect of physic of failure , effectively saving time and cost.