A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from low-frequency passive microwave observations. The error estimate is based on a basic error propagation equation which uses the partial derivatives of the radiative transfer equation and estimated errors for each individual input parameter. Results similar to those of the Monte Carlo approach show that the developed time-efficient methodology could substitute computationally intensive methods. This procedure is therefore a welcome solution for near-real-time data assimilation studies where both the soil moisture product and error estimate are needed. The developed method is applied to the C-, X-, and Ku-bands of the Aqua/Advanced Microwave Scanning Radiometer for Earth Observing System sensor to study differences in errors between frequencies.