Metabolic dysfunction-associated steatohepatitis (MASH) is a disease characterized by accumulation of fat droplets and fibrous tissue in the liver. This disease has attracted attention due to its high incidence and risk of severe complications. High-frequency quantitative ultrasound (QUS) has demonstrated strong potential in the diagnosis of liver diseases. However, previous studies focused only on evaluating lipid droplets in fatty liver, without accounting for the interference of other components such as fibrous tissue. This study aimed to clarify the scattered signals from various tissues by analyzing six numerical computer phantoms simulating normal liver, fatty liver and hepatitis, using an amplitude envelope statistical method, the double Nakagami (DN) model. The simulation system consisted of an ultrasound platform and a linear probe with center frequency of 31.25 MHz. Eleven plane waves ranging from −15° to +15° were transmitted and received using a compound plane-wave imaging method. The results show that the DN model matches the amplitude envelope of the original echo signals and effectively distinguishes independent signal components arising from different tissues. In fatty liver phantoms, the DN model parameter αω_F showed a strong positive correlation (r = 0.8434, p = 0.0472) with fat volume. In hepatitis phantoms, αω_F increased with increase in the fibrous tissue mixture ratio in the regions of interest, while μ_L, μ_F were close to 1, reflecting the cell distribution patterns and tissue characteristics. These results indicate that echo signals exhibit different properties when the scatterer density is high or when scattering intensity is strong, supporting the feasibility of using the DN model to differentiate fat and fibrous tissues from normal liver. However, real clinical cases are more complex, as fatty and fibrous tissue intermix in the liver, requiring further validation in the future. Nevertheless, the results show the potential of this method for real-time, noninvasive quantitative characterization of tissue properties.