Hepatic fibrosis stage is the most important determinant of outcomes in patients with non-alcoholic fatty liver disease (NAFLD). There is an urgent need for non-invasive tests that can accurately stage fibrosis and determine efficacy of interventions. Here we describe a novel cf-mRNA-Sequencing approach that can accurately and reproducibly profile low levels of circulating mRNAs and evaluate the feasibility of developing a cf-mRNA-based NAFLD fibrosis classifier. Using separate discovery and validation cohorts with biopsy-confirmed NAFLD (n=176 and 59, respectively) and healthy subjects (n=23), we performed serum cf-mRNA RNA-Seq profiling. Differential expression analysis identified 2498 dysregulated genes between NAFLD and healthy subjects and 134 fibrosis-associated genes in NAFLD patients. Comparison between cf-mRNA and liver tissues transcripts revealed significant overlap of fibrosis associated genes and pathways indicating that the circulating cf-mRNA transcriptome reflects molecular changes in the livers of NAFLD patients. In particular, metabolic and immune pathways reflective of known underlying steatosis and inflammation were highly dysregulated in the cf-mRNA profile of patients with advanced fibrosis. Finally, we used an elastic net ordinal logistic model to develop a classifier that predicts clinically significant fibrosis (F2-4). In an independent cohort, the cf-mRNA classifier was able to identify 50% of patients with at least 90% probability of clinically significant fibrosis. We demonstrate a novel and robust cf-mRNA-based RNA-Seq platform for non-invasive identification of diverse hepatic molecular disruptions and for fibrosis staging with promising potential for clinical trials and clinical practice.