An important parameter in asynchronous transfer model (ATM)-based network design and management is the cell loss ratio (CLR) in ATM multiplexers. It is a key parameter to many vital functions in the network such as call admission control (CAC), bandwidth allocation, etc. However, the CLR depends usually on many unknown and unpredictable traffic parameters such as input traffic correlations. In this paper, we propose a simple and robust fuzzy-based algorithm to predict the CLR in large-sized systems based on both a small amount of information from small-sized systems, and the asymptotic behavior for very large systems. Unlike the model-based approaches, our approximation avoids the problem of assuming any traffic parameters or arrival process. This algorithm is used with real-time traffic measurement to propose an effective measurement-based call admission control framework for ATM networks.