The early stages of nonalcoholic fatty liver disease (NAFLD) are characterized by the accumulation of fat in the liver (steatosis). This can lead to cell injury and inflammation resulting in nonalcoholic steatohepatitis (NASH). To determine whether lipid profiling of liver tissue can identify metabolic signatures associated with disease presence and severity, we explored liquid extraction surface analysis mass spectrometry (LESA-MS) as a novel sampling tool. Using LESA-MS, lipids were extracted directly from the surface of ultrathin slices of liver tissue prior to detection by high-resolution mass spectrometry (MS). An isotopically labeled internal standard mix was incorporated into the extraction solvent to attain semiquantitative data. Data mining and multivariate statistics were employed to evaluate the generated lipid profiles and abundances. With this approach, we were able to differentiate healthy and NAFLD liver in mouse and human tissue samples, finding several triacylglyceride (TAG) and free fatty acid (FFA) species to be significantly increased. Furthermore, LESA-MS was able to successfully differentiate between simple steatosis and more severe NASH, based on a set of short-chain TAGs and FFAs. We compared the data obtained by LESA-MS to that from liquid chromatography (LC)-MS and matrix-assisted laser desorption ionization MS. Advantages of LESA-MS include rapid analysis, minimal sample preparation, and high lipid coverage. Furthermore, since tissue slices are routinely used for diagnostics in clinical settings, LESA-MS is ideally placed to complement traditional histology. Overall LESA-MS is found to be a robust, fast, and discriminating approach for determining NAFLD presence and severity in clinical samples.