Nano-precipitate strengthened alloys, including Inconel 718 or a recently developed series of FCC austenitic steels are considered ideal candidate materials to meet highest standards in strength, fatigue resistance, and corrosion protection without compromising ductility. However, predicting mechanical properties resulting from microstructural changes and processing conditions constitute a substantial challenge. Many existing models rely on experimentally measured, macroscale level mechanical properties. Therefore, these approaches cannot provide an explanation or even predictive capabilities for the unique mechanical property combinations observed in some of these alloys especially for additive manufacturing. The chemical complexity of these alloys involving small sizes of the particles on the order of few nm severely complicates the physically based prediction of macroscale mechanical properties induced by the characteristics of the particles and their ensembles using meso-scale modeling, such as Discrete Dislocation Dynamics (DDD). We therefore develop a coarse-grained approach for predicting a representative critical resolved shear stress (CRSS) inside local volume elements following the percolation idea for flow-stress from Kocks and Mecking. Informed by atomistic simulations (DFT/MD), atom probe tomography, and meso-scale modeling of dislocation-precipitate interaction, we present a unique coarse-graining approach in predicting material yield strength for materials with nanoprecipitates. Using this approach, we model realistic nano-precipitate size distributions in large scale Discrete Dislocation Dynamics (DDD) simulations with the aim of predicting macroscale mechanical properties. This demonstrates a pathway to fill the gap in modeling plastic deformation phenomena in nano-precipitate strengthened alloys incorporating chemical heterogeneities between nanoscale effects and resulting mechanical properties.