Aligned nanorod inclusions have the potential to significantly improve both the photovoltaic and mechanical properties of polymeric materials. Establishing facile methods for driving or “corralling” the nanorods to self-assemble into such aligned morphologies could facilitate the fabrication of effective, robust devices. Using a variety of computational methods, we model the self-assembly of a mixture of A-coated and B-coated rods in an AB phase-separating blend. Using dissipative particle dynamics (DPD) simulations, we first show that the steric repulsion between ligands causes the coated rods to preferentially align end-to-end within the minority phase of the binary blend. Using this information, we then utilize a coarse-grained approach, which combines a Cahn–Hilliard (CH) model for the polymer blend with a Brownian dynamics (BD) simulation for the rods, to simulate a larger sample of a rod-filled 30 : 70 AB thin film. We find that just a small volume fraction of B rods in the majority B phase promotes the percolation of A-like rods within A, so that the percolation threshold for the A-rods is significantly lowered. If, however, the number of Bnanorods in the B phase exceeds a particular volume fraction, the B particles inhibit the percolation of the A rods. Thus, there is an optimal volume fraction of Bnanorods that provides the beneficial effects. The output from these morphological studies then serves as the input to the lattice spring model (LSM) for mechanical behavior of the composite. The results reveal that nanorods oriented along the tensile direction contribute to the enhancement of the macroscopic mechanical properties of the material. This multi-scale approach, integrating techniques that cover the microscopic, mesoscopic and macroscopic, provides a valuable means of determining structure–property relationships in nanocomposites and establishing useful guidelines for tailoring the components to yield optimal materials' properties.