Spinodal decomposition can improve a number of essential properties in materials, especially hardness. Yet, the theoretical prediction of the onset of this phenomenon (e.g., temperature) and its microstructure (e.g., wavelength) often requires input parameters coming from costly and time-consuming experimental efforts, hindering rational materials optimization. Here, we present a procedure where such parameters are not derived from experiments. First, we calculate the spinodal temperature by modeling nucleation in the solid solution while approaching the spinode boundary. Then, we compute the spinodal wavelength self-consistently using a few reasonable approximations. Our results show remarkable agreement with experiments and, for NiRh, the calculated yield strength due to spinodal microstructures surpasses even those of Ni-based superalloys. We believe that this procedure will accelerate the exploration of the complex materials experiencing spinodal decomposition, critical for their macroscopic properties.