Methods and apparatus for anomaly detection in network-site metrics using predictive modeling are described. A method comprises obtaining time-series data for a given time range, wherein the time-series data comprises values for a network-site analytics metric for each of a plurality of sequential time steps across the given time range. The method includes generating a predictive model for the network-site analytics metric based on at least a segment of the time-series data. The method includes using the predictive model to predict an expected value range for the network-site analytics metric for a next time step after the segment and, based on the expected value range, determining whether an actual value for the network-site analytics metric for the next time step is an anomalous value.