In this paper, a new information theoretic algorithm is proposed for signal enumeration in DS-CDMA networks. The approach is based on the predictive description length (PDL) of the observation vector. The PDL is the length of a predictive code of observations. For signal detection, the PDL criterion is computed for the candidate models and is minimized to determine the number of signals. The proposed technique uses the maximum likelihood (ML) estimate of the correlation matrix. The only information used in the ML estimation of the correlation matrix is the multiplicity of the smallest eigenvalue. The PDL algorithm has a signal-to-noise ratio resolution threshold that is smaller than that of the minimum description length (MDL). The proposed method can be used on-line and can be applied to time-varying and non-stationary systems.