The research presented in this paper tackles the problem of estimating blocking probabilities in a multiservice loss system via simulation. This approach uses the static Monte Carlo simulation method and applies two importance sampling methods, namely, inverse convolution and Gaussian distribution. The results obtained for the examples presented confirm the importance of the proposed methods. The work relates to Mandjes’s work on using importance sampling with exponentially twisted distributions [1]. However, it is further extended and improved with two effective importance sampling methods, which very closely approximate the generation of samples with the ideal importance sampling distribution. The ideas and methods presented are quite significant. The work documents the proposed methods using suitable mathematical terms and equations, and sufficient numerical examples, to prove its significance. However, further practical case studies could have been provided to justify its intended use.