Abstract: Nanofluids, recognized as advanced media for heat and mass transfer, have demonstrated substantial potential across diverse engineering applications, particularly in scenarios demanding enhanced thermal management and improved energy efficiency. Nevertheless, their deployment relies on the precise characterization of thermophysical properties governed by nanoscale phenomena, including particle size, morphology, dispersion stability, and interfacial dynamics. This paper presents an analysis that integrates experimental observations, multiscale theoretical frameworks, and empirical correlations to investigate how nanoparticle size influences the effective thermal conductivity and dynamic viscosity, while also examining the roles of particle shape factor, volume fraction, temperature, phonon matching, and aggregation dynamics. The experimental results confirm that the thermal conductivity increases as the particle size decreases and the volume fraction increases, owing to the elevated surface-to-volume ratio and intensified Brownian motion-induced microconvection. This effect is further amplified at higher temperatures, which enhances the Brownian activity. A pronounced nonmonotonic relationship emerges, revealing an optimal particle diameter of approximately 50 nm at which ballistic phonon transport—activated when the particle dimensions approach the phonon mean free path of the base fluid—minimizes interfacial thermal resistance and maximizes heat transfer. Nanoparticles smaller than this threshold incur excessive interface scattering, which limits conductivity, whereas larger particles exhibit weakened Brownian contributions and greater sedimentation tendencies. Additionally, phonon frequency matching between the nanoparticle and the base fluid has been shown to critically affect thermal transport, such that even materials with lower intrinsic conductivity can yield superior performance when well matched. Beyond conductivity, nanoparticle aggregation at high volume fractions forms fractal-like conductive networks that further boost heat transfer but simultaneously increase viscosity through intensified hydrodynamic drag and interparticle friction, underscoring the importance of optimizing both particle concentration and aggregation state. Viscosity measurements revealed that the dynamic viscosity increased with the volume fraction and decreased with the temperature, reflecting enhanced particle interactions and reduced Brownian mobility under high loading and low thermal conditions. While most studies, including this one, observed that the viscosity increases with the particle size, primarily owing to enhanced hydrodynamic resistance, certain investigations demonstrated that exceptionally small particles may also elevate the viscosity because their high surface-to-volume ratios intensify interfacial molecular ordering and localized shear effects. These discrepancies are largely attributable to variations in dispersion stability and aggregation kinetics, with poorly stabilized suspensions showing significant viscosity deviations compared with well-dispersed systems. Classical theoretical models, such as the Maxwell–Garnett and Bruggeman models, are inadequate for capturing these complex behaviors because they ignore size-dependent interfacial effects and dynamic particle–fluid coupling, whereas empirical correlations that incorporate particle size parameters, temperature-dependent Brownian coefficients, and aggregation dynamics achieve prediction errors below 8% across diverse compositions. Sensitivity analyses demonstrated that slight deviations in the nanoparticle diameter could shift the optimal performance thresholds, highlighting the necessity for precise size control during synthesis. Furthermore, preliminary comparisons among spherical, rod-like, and plate-shaped particles suggest that the morphology can modulate both the thermal conductivity and viscosity, with cubic or high-aspect-ratio geometries offering enhanced conductivity at similar volume fractions but exhibiting limited influence on the viscosity at low loadings. By systematically mapping the interdependencies among nanoparticle size, thermal conductivity, viscosity, phonon matching, and aggregation, this study advances actionable strategies for optimized nanofluid design, including recommendations for maintaining moderate volume concentrations of optimally sized particles, employing surface functionalization to stabilize dispersions, and exploring hybrid particle systems to decouple thermal and viscous responses.