This paper addresses the problem of estimating the roll-off factor of a received communication signal. We study two new statistical estimation methods that determine the roll-off factor by minimizing the difference between the theoretical and empirical power or power spectral density of the received signal. Another interesting contribution is the derivation of the roll-off Cramér–Rao bound which provides a reference in terms of estimation variance. Simulation results conducted on synthetic data allow the performance of the proposed methods to be evaluated. They are compared to a recent technique based on the amplitude fluctuations of the power spectral density associated with the received communication signal. The estimation methods are shown to be robust to channel impairments (including white Gaussian noise and synchronization errors). The proposedstrategies are finally tested communication problems.on real signals with known ground truth showing their possible application to digital