This feasibility study evaluates an approach for prediction of sandstone plug porosity and permeability based on low-angle illumination imaging, the Angle Measure Technique (AMT) and chemometric multivariate calibration/validation. The AMT approach transforms 2-D texture images of drill core plug ends into 1-D ‘complexity spectra’ in which inherent porosity- and permeability-correlated features are subsequently extracted and subjected to multivariate calibration modelling. A training data set was selected because of its wide-spanning porosity and permeability ranges allowing evaluation of realistic prediction performance for typical North Sea/Scandinavian sandstone oil/gas reservoir rocks. This first study makes use of sand stone plugs from a single drill core from the Danish underground. Contingent upon proper test set validation (deliberately not deleting a few small, potential outliers), prediction performance assessment were for porosity [%] slope: 0.86; RMSEP: 2.2%; R2 = 0.90 and for permeability [mDarcy]: slope: 0.91; RMSEP: 458 mDarcy; R2 = 0.87, which translates into RMSEPrel of 12% and 19% respectively. These results pertain to a typical, well-spanning training data set (18 sandstone plugs); it is therefore concluded that the AMT approach to poro-perm prediction from images is feasible, but further, extended calibrations must be based on a more comprehensive training data sets covering the full geological regime of reservoir sandstones. We discuss possible application potentials and limitations of this approach.