A variety of material properties have been shown to be well characterized by multimodal distribution functions. Traditional statistical modeling has been relatively simplistic, i.e., a unimodal distribution has been proposed. Upon closer inspection, however, multiple modes may be exhibited in the material property. With the development of advanced experimental testing procedures, more statistically complicated multimodal characteristics have been observed. The purpose of this presentation is to demonstrate the use of standard and innovative statistical modeling methodologies for multimodal materials characterization. Illustrations for modeling multimodal behavior are developed from data from diverse materials used in various applications, e.g., porosity in additive manufacturing, fatigue crack size, and fatigue life. While the methodology for constructing appropriate distributions is applicable for all classes of underlying distributions, the examples that are investigated will utilize the Weibull distribution for the modes.