This paper addresses optimal online estimation of the size of a multicast group. Three distinct approaches are used. The first one builds on Kalman filter theory to derive the MSE-optimal estimator in a heavy-traffic regime. Under more general assumptions, the second approach uses Wiener filter theory to compute the MSE-optimal linear filter. The third approach develops the best first-order linear filter from which an estimator that holds for any on-time distribution is derived. Our estimators are tested on real video traces and exhibit good performance. The paper also provides guidelines on how to tune the parameters involved in the schemes in order to achieve high-quality estimation while simultaneously avoiding feedback implosion.