Predictions of solute transport in subsurface environments are notoriously unreliable due to aquifer heterogeneity and uncertainty about the values of hydraulic parameters. Probabilistic framework, which treats the relevant parameters and solute concentrations as random fields, allows for quantification of this predictive uncertainty. By providing deterministic equations for either probability density function or cumulative distribution function (CDF) of predicted concentrations, the method of distributions enables one to estimate, e.g., the probability of a contaminant’s concentration exceeding a safe dose. We derive a deterministic equation for the CDF of solute concentration, which accounts for uncertainty in flow velocity and initial conditions. The coefficients in this equation are expressed in terms of the mean and variance of concentration. The accuracy and robustness of the CDF equations are analyzed by comparing their predictions with those obtained with Monte Carlo simulations and an assumed beta CDF.