As wireless networks have become more complex with packet services and sophisticated modulation techniques, validation using multidimensional Markov Chain models has become increasingly rare. Although Product Form models fail when queued packet services are introduced, iterative models (such as Gauss-Seidel) can be accurate. However, Gauss- Seidel is memory and processor intensive. This study considers whether probabilistic transitions can replace state variables in reducing the size of the Gauss-Seidel matrix, while modeling wireless load sharing algorithms including packet services, such as could be used in seamless 4G networks. The model is validated against simulation. Performance results are discussed for load shared networks involving heterogeneous queued packet services alone or in combination with speech services.