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Coarse aggregate sources must possess sufficient level of quality to meet both initial design as well as long-term and life-cycle performance requirements for pavement construction. Morphological shape properties, mineralogy, and chemical properties of the aggregate particles can significantly influence their quality and performance in terms of both durability and mechanical properties. As part of this study, a survey was sent out to different highway agencies to collect representative coarse aggregate samples as well as information regarding different practices used by them for morphological, petrographic, and chemical characterizations of aggregate sources. Morphology analysis using machine vision technology was incorporated to identify shape properties of the collected aggregate samples. Additionally, thin section optical petrographic analysis using an Axioscan 7 full slide scanner was utilized to identify mineral composition of the aggregates. Finally, chemical testing and analysis was conducted using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) to detect major element compositions in epoxy impregnated sample of aggregate particles. Statistical analysis including Pearson correlation and multiple regression were deployed to investigate the relationship between the parameters representing mineralogy, chemical, and morphological shape properties. The findings of this study indicated 12 minerals and seven chemical elements with statistical significance to impact the imaging-based shape indices of aggregates. Subsequently, regression-based prediction models were developed to estimate the aggregate shape indices using mineralogy and chemical properties with a relatively satisfactory performance. The improvements in objectively characterizing aggregate chemical, mineralogical, and shape properties can be used to develop improved and sustainable aggregate production methods and specifications.