Time-of-flight secondary ion mass spectrometry (TOF-SIMS) negative and positive spectral fragmentation patterns acquired from a series of samples taken at various times during the assembly of dodecanethiol on gold were analyzed using principal components analysis (PCA). This analysis allowed exploration of the entire spectrum, thereby eliminating peak choice bias and permitting the elucidation of trends not apparent from univariate analysis. PCA results showed trends in the data that give insight into the fragmentation process of assembled monolayer surfaces. Long assembly times corresponded with a series of short hydrocarbon fragments hypothesized to originate from the headgroup region of the thiol molecules (C-, CH-, CH2-, C-2(-), C2H-, C2H3-, C-3(-), C3H-, C3H2-) and with key molecular ion clusters emitted from the gold surface ([M - H](-), AuM-, Au-2[M - H](-), and Au[M - H)(2)(-), where M = HSC12H25). Similar trends were seen in the positive ion spectral data. This information was used to create a multivariate ratio of peaks that correlated across several different thiol self-assembled monolayers (SAMs) with the parachor and the cohesive energy density of the different thiols. A model for SAM fragmentation by SIMS is proposed based on the PCA. This study demonstrates the power of multivariate analysis of TOF-SIMS data for interpreting spectra and maximizing the information content from SIMS analysis of complex surfaces.