The aim of this study was to develop a structure-property model for membrane partitioning of oligopeptides using statistical design methods and multivariate data analysis. A set of 20 tetrapeptides with optional N-methylations at residues 2 and 4 was designed by a D-optimal design procedure. After synthesis and purification, the membrane partitioning abilities of the peptides were tested in two chromatographic systems with phospholipids as the stationary phase: immobilized artificial membrane chromatography (IAM) and immobilized liposome chromatography (ILC). The relationship between these measures and three different sets of calculated descriptors was analyzed by partial least-squares projection to latent structures (PLS). The descriptors used were the molecular surface area, Molsurf parameters, and Volsurf parameters. All three models were of good statistical quality and supported that a large hydrogen-bonding potential and the presence of a negative charge impair membrane partitioning, whereas hydrophobic parameters promote partitioning. The findings are in accordance with what has been found for absorption of known drugs and have implications for the design of peptide-like drugs with good oral bioavailability.