Pathologists use a semiquantitative scoring system (NAS or SAF score) to facilitate the reporting of disease severity and evolution. Similar scores are applied for the same purposes in rodents. Histological scores have inherent inter- and intra-observer variability and yield discrete and not continuous values. Here we performed an automatic numerical quantification of NASH features on liver sections in common preclinical NAFLD/NASH models. High-fat diet-fed foz/foz mice (Foz HF) or wild-type mice (WT HF) known to develop progressive NASH or an uncomplicated steatosis, respectively, and C57Bl6 mice fed a choline-deficient high-fat diet (CDAA) to induce steatohepatitis were analyzed at various time points. Automated software image analysis of steatosis, inflammation, and fibrosis was performed on digital images from entire liver sections. Data obtained were compared with the NAS score, biochemical quantification, and gene expression. As histologically assessed, WT HF mice had normal liver up to week 34 when they harbor mild steatosis with if any, little inflammation. Foz HF mice exhibited grade 2 steatosis as early as week 4, grade 3 steatosis at week 12 up to week 34; inflammation and ballooning increased gradually with time. Automated measurement of steatosis (macrovesicular steatosis area) revealed a strong correlation with steatosis scores (r = 0.89), micro-CT liver density, liver lipid content (r = 0.89), and gene expression of CD36 (r = 0.87). Automatic assessment of the number of F4/80-immunolabelled crown-like structures strongly correlated with conventional inflammatory scores (r = 0.79). In Foz HF mice, collagen deposition, evident at week 20 and progressing at week 34, was automatically quantified on picrosirius red-stained entire liver sections. The automated procedure also faithfully captured and quantitated macrovesicular steatosis, mixed inflammation, and pericellular fibrosis in CDAA-induced steatohepatitis. In conclusion, the automatic numerical analysis represents a promising quantitative method to rapidly monitor NAFLD activity with high-throughput in large preclinical studies and for accurate monitoring of disease evolution.