A key target of the Circular Plastic Alliance Declaration is to include 10 million tons of recycled plastic per year into new plastic products in Europe by 2025. To meet this objective mechanical recycling has to overcome two main obstacles. First, new reliable, and cost-efficient technologies with high material separation accuracy are required. Secondly, the quality and performance of recyclates must be improved significantly. Polyethylene (PE) is a globally dominant polymer as a result of its wide range of variations in molecular structure and morphology. State-of-the-art near infrared (NIR) sorting systems easily identify base materials, but they can hardly account for specific characteristics in the molecular structure of PE. The processability and applicability of such recycled materials for high quality applications is limited due to the wide range of variation in the chemical structure of PE grades, e.g. molar mass and molar mass distribution or short and long chain branching. The main aim of this paper is to separate the post-consumer PE into various classes based on specific molecular characteristics, like density or melt flow rate. In a first step different PE types have been investigated using Infrared and Raman spectroscopy and the resulting spectra have been evaluated using multivariate data analysis (MVDA). Applying multivariate data analysis (MVDA) on spectroscopy data allowed the prediction of density. The results showed a good agreement with the measured values, where the calculated densities showed a less than 0.5% deviation from the measured values, indicating that processing relevant information can be extracted from FTIR and Raman data. In a second step the PE samples were measured on a state of the art NIR based sorting line. In a first analysis the PE samples could be classified with respect to its processing methods. However, this work is still ongoing and the model still needs to be improved. The results indicate that existing NIR sorting lines can be used for further differentiation of post consumer plastics based on specific molecular features, which would results in an improved quality of the recycled material.