Solid recovered fuels are highly heterogeneous mixtures generated from high calorific fractions of nonhazardous waste materials intended to be fired in existing coal power plants and industrial furnaces ( CEN/ TC 343 N 9rev3, Solid Recovered Fuel, 2003). These materials are commonly irregular in shape and size. It is therefore not easy to predict their aerodynamic properties, especially in comparison to pulverized fuels. Because particles fall with their maximum projection area perpendicular to the direction of the fall, a size measure representing this maximum projection area is most likely to relate to behavioral properties ( Sneed, E D.; Folk, R. L. J. Geol. 1958, 66, 114- 150). In view of this, the ability to describe precisely the largest projected area of a particle will immensely help in any modeling of particles' behavior in boilers and industrial furnaces. The particle image analysis method ( PIAM) is an automatic image processing tool developed with MATLAB-coded commands that is capable of determining several properties of irregular- shaped particles including the largest projected area, equivalent diameter of a sphere of the same projected area and mass, major and minor axis lengths of each particle, eccentricity, and many more. PIAM processes digital images of particles to determine their properties in terms of picture elements ( pixels). With the magnification factor, pixel distances can be converted into real distances. The particle information obtained from PIAM is used to characterize behavioral properties.