Previous objective front algorithms have identified fronts as a linear boundary located on the warm side of a strong thermal gradient. However, while this follows conventional frontal depiction, fronts are essentially transition zones between two air masses and might benefit from being depicted as such rather than a definitive boundary. To this end, a method to identify, characterize, and classify frontal zones in numerical model forecast output has been developed. This approach adopts elements from existing algorithms and combines them in an innovative way. Several examples illustrating the utility of this technique will be presented. Preliminary results have been encouraging when compared with manual analyses, particularly in regards to the identification of cold and warm frontal zones.