The multifactor version of Copula models is useful in fitting the complex correlation structure among the base portfolio of CDOs. However, plain Monte Carlo simulation is quite incapable of accurately measuring rare but significant loss events. We provide a fast numerical inversion of conditional Laplace transform in multifactor models.The method is capable of estimating loss probability P(L>y) and expected loss E[L∧y].Numerical examples illustrate the efficiency of the method, especially when handling rare events.