Nonalcoholic steatohepatitis (NASH) is an emerging health problem worldwide. However, efficacious pharmacological treatment for NASH is lacking. A major issue for preclinical evaluation of potential therapeutics for NASH is the limited number of appropriate animal models, i.e., models that do not require long-term dietary intervention and adequately mimic disease progression in humans. The present study aimed to evaluate a 3-wk dietary mouse model of NASH and validate it by studying the effects of liraglutide, a compound in advanced clinical development for NASH. C57BL6/J mice were fed a diet high in fat (60%), cholesterol (1.25%), and cholic acid (0.5%), along with 2% hydroxypropyl-β-cyclodextrin in drinking water (HFCC-CDX diet). Histological and biological parameters were measured at 1 and 3 wk. After 1-wk diet induction, liraglutide was administrated daily for 2 wk and then NASH-associated phenotypic aspects were evaluated in comparison with control mice. Prior to treatment with liraglutide, mice fed the HFCC-CDX diet for 1 wk developed liver steatosis and had increased levels of oxidative-stress markers and hepatic and systemic inflammation. For mice not treated with liraglutide, these aspects were even more pronounced after 3 wk of the dietary period, with additional liver insulin resistance and fibrosis. Liraglutide treatment corrected the diet-induced alterations in glucose metabolism and significantly reduced hepatic steatosis and inflammation. This study provides a novel 3-wk dietary model of mice that rapidly develop NASH features, and this model will be suitable for evaluating the therapeutic efficacy of compounds in preclinical drug development for NASH. We propose a diet high in fat (60%), cholesterol (1.25%), and cholic acid (0.5%) along with 2% hydroxypropyl-β-cyclodextrin in drinking water (HFCC-CDX diet) as a new dietary model of nonalcoholic steatohepatitis. We used the HFCC-CDX model to reproduce the main features of disease development in humans for the purpose of facilitating the rapid screening of drug candidates and prioritizing the more promising candidates for advanced preclinical assessment and subsequent clinical trials.