We propose an asymptotically unbiased and consistent estimate of the bispectrum of a stationary continuous-time process X = {X(t)} t∈R . The estimate is constructed from observations obtained by a random sampling of the time by {X(τ k )} k∈Z , where {τ k } k∈Z is a sequence of real random variables, generated from a Poisson counting process. Moreover, we establish the asymptotic normality of the constructed estimate.