Rational design of chemical composition of ferrite with spinel structure used to be a challenge due to its multivariate nature. Over ten kinds of tetrahedral interstitial cation elements and multi-step processing routes have complex interactions and different contributions to the final magnetic, electronics and electrical properties. Informatics based approach for exploring material property space has the potential to mitigate the costs, risks, and time involved in the actual preparation and testing of potentially useful materials, and could yield valuable insights into the fundamental factors underlying materials behavior. Materials Informatics represents this kind of rational strategy to systematically navigate through materials structure/property space, and involves a variety of computational methodologies to generate and analyze scientific and engineering materials data. In this study, an informatics technology, implementing Principal Component Analysis (PCA) and Rough Set (RS) theory is applied to model the chemical composition space of spinel ferrite for better performance in terms of low conductivity even at high frequency with good magnetic property.