In this study we applied statistical multivariate analysis techniques to establish correlations between material properties and tablet tensile strength (TS) of microcrystalline cellulose (MCC) with different types and manufacturers. There were sixteen MCC samples included in this analysis described by 22 material parameters. For data analysis, principal component analysis (PCA) was used to model and evaluate the various relationships between the material properties and TS. Furthermore, partial least squares regression (PLS) analysis was performed to quantify the relationships between the material properties and TS and to predict the most influential MCC parameters contributing to the compactibility. The results showed that the moisture content, hygroscopicity and crystallinity did not exhibit significant impact on TS. The turgidity, maximum water uptake, degree of polymerization and molecular weight presented a strong positive influence on TS, while the density property, bulk and tap density, exhibited an obvious negative impact. The present work demonstrated that multivariate data analysis techniques (PCA and PLS) are useful for interpreting complex relations between 22 material properties and the tabletting properties of MCC. Furthermore, the method can be used for material classification.