In the field of 'single cell analysis', many classical strategies like immunofluorescence and electron microscopy are the primary techniques of choice. However, these methodologies are time consuming and do not permit direct identification of specific molecular classes, such as lipids. In the present study, a novel mass spectrometry-based analytical approach was applied to bovine oocytes and embryos. This new metabolomics-based application uses mass spectrometry imaging (MSI), efficient data processing and multivariate data analysis. Metabolic fingerprinting (MF) was applied to the analysis of unfertilised oocytes, 2-, 4- and 8-cell embryos and blastocysts. A semiquantitative strategy for sphingomyelin [SM (16:0)+Na](+) (m/z 725) and phosphatidylcholine [PC (32:0)+Na](+) (m/z 756) was developed, showing that lipid concentration was useful for selecting the best metabolic biomarkers. This study demonstrates that a combination of MF, MSI features and chemometric analysis can be applied to discriminate cell stages, characterising specific biomarkers and relating them to developmental pathways. This information furthers our understanding of fertilisation and preimplantation events during bovine embryo development.