One of the most important collective communication patterns used in scientific applications is the complete exchange, also called All-to-All. Although efficient complete exchange algorithms have been studied for specific networks, general solutions like those available in well-known MPI distributions (e.g. the MPI_Alltoall operation) are strongly influenced by the congestion of network resources. In this paper we present an integrated approach to model the performance of the All-to-All collective operation. Our approach consists in identifying a contention signature that characterizes a given network environment, using it to augment a contention-free communication model. This approach allows an accurate prediction of the performance of the All-to-All operation over different network architectures with a small overhead. This approach is assessed by experimental results using three different network architectures, namely Fast Ethernet, Gigabit Ethernet and Myrinet.