A maximum likelihood estimation (MLE) method for simultaneously retrieving wind and rain from SeaWinds scatterometer data is introduced and evaluated. The new method incorporates rain backscatter and attenuation into the retrieval process via a simple wind/rain backscatter model. Two retrieval methods are examined: First, when no estimate of the rain rate is available, the new MLE method simultaneously estimates wind speed, wind direction and rain rate. Second, when an estimate of the rain is available, the wind is retrieved by directly correcting the geophysical model function using the rain/wind backscatter model. From simulation, the simultaneous wind/rain retrieval approach demonstrates improved wind vector estimates where the rain is significant. The improvement in retrieval is more pronounced in the “sweet spot” of SeaWinds’ cross track. The rain-corrected wind retrieval approach gives somewhat improved wind speed estimates for rain-contaminated wind vectors over the simultaneous wind/rain retrieval method, especially when the effect of rain is small. Validation of the SeaWinds rain data with co-located Tropical Rainfall Measuring Mission precipitation radar rain rates shows that with some limitations the SeaWinds scatterometer can measure rain.