In LemnaGrid, users can analyze images using pre-defined functions. The advantage is that you can do the programming on a graphical surface, without the demand for command-line programming. So, it is easy to learn, and you don’t need to be a software engineer to analyze images. In the newest version of LemnaGrid, machine learning becomes available for the users. As image processing not always succeeds with classical tools, machine learning broadens the range of applications, and users can train the algorithms so that they recognize specific phenotypic traits. With machine learning, image processing becomes more application-oriented and case specific. The new LemnaGrid provides pre-set models in machine learning that are ready to use. In addition, LemnaTec offers to develop custom models, which can be integrated and used in LemnaGrid. In a LemnaGrid Plus version, users can develop their own models. This is the most flexible option that offers the broadest functionality to the users. For instance, it can serve to count leaves, and improves analyses in case of are occlusions or overlaps. More applications, particularly in plant stress and diseases, root analysis, or quality trait analysis are enabled.