New generation composites are critical for further innovation and technological breakthroughs. Reinforced composite materials have immense potential as multifunctional high-performance materials due to their highly adjustable mechanical, thermal and electrical properties. However, the full advantages of these materials are not realized due to the inability to properly predict performance strictly from constituent properties. Using a statistical approach along with Weibull fracture mechanics, ideal and tailored targeted properties can be more effectively predicted and controlled. Using a “certification by analysis” approach that engages computational power to predict rigorous coupon testing, this obstacle for new material utilization in the market can be reduced, saving time and money. This physics-based method can be employed not only with larger parts, but also is effective to understand microstructures and use this knowledge toward improving the manufacturing processes that shape these composites. Precise characterization of the resin is crucial due to the highly sensitive time/temperature relationship of the resin and influences interfacial properties and coefficient of thermal expansion mismatches of constituent materials. These projects will address the needs for industrial nanomaterials at multiple scales by pairing simulation and experiment that combine into a digital twin to unwrap innovative possibilities.