Nanoparticle-technology was employed to address the challenges of asphaltene precipitation during oil production. Fe3O4 and NiO nanoparticles were synthesized and characterized. Asphaltene was extracted and dissolved in toluene to prepare reservoir model oil. The asphaltene precipitation onset in the presence and absence of the nanoparticles by the addition of n-heptane was measured using dynamic light scattering. Cubic plus association equation of state (CPA EoS) was employed to predict the asphaltene precipitation in the presence and absence of the nanoparticles. The CPA EoS determines the precipitate amount of the asphaltene by knowing the asphaltene average aggregate size in the liquid. In the presence of the nanoparticles, the asphaltene self-association energy is inferred to be a function of the molar density of the surface sites of the nanoparticles with an exponential relationship. The CPA EoS can be employed for designing chemical inhibitors of the asphaltene precipitation by the metal oxides nanoparticles.