Besides the challenging extraction of microplastics from diverse matrices and their chemical analysis, it is also tricky to quantify particle sizes and shapes accurately. By checking particle size data of different studies, it becomes evidential that the data are hardly comparable. This is mainly due to the different techniques and modes of displaying particle size distributions (PSD), additionally to the non-conform sampling strategies and statistical variations. Drawbacks of the common methods are limits in sample numbers, analytical speed, complexity in handling, inefficiency or non-repeatability by destructive methods. Furthermore, non-reliable information on shape by simplifying measurements applying the concept of equivalent spheres are inappropriate for irregular shaped particles as fibers. We developed an ImageJ plugin, a Matlab code and a self-written Processing tool to test best practice in particle analysis for a series of scanning electron microscope images of polyethylene particles (PE) and polyethylene terephthalate (PET) fibers. The prerequisite was to run large data sets at once in a short time. To consider the irregularity of particles, the reciprocal aspect ratio and feret major axis ratio was calculated. As reference, we used manually corrected images, whereby particle overlaps, artifacts or missing particle segments were elaborately processed for each image separately. For PET fibers, results show that Matlab and ImageJ have a significantly greater deviation than Processing Tool caused by conglomerations detecting fewer fibers than actually present. Interestingly the Matlab results for PE particles are much closer to the reference value than those generated with ImageJ or Processing Tool. We conclude that the appropriate software should be chosen depending on the application and the object(s) to be viewed, because considerable variations may occur based on the specifics of the programs itself. Nevertheless, PSDs and shapes for the present microplastics can be determined for all three methods quickly and accurately in good agreement.