This study introduces an automated analysis workflow to quantify kidney regeneration over time in the developing zebrafish upon automated laser-induced injury on a screening microscope equipped with a photomanipulation module. The screening dataset consists of multiple time-lapse images of injured and fluorescently labelled distal pronephric tubules of the transgenic Tg(cdh17:egfp) zebrafish line. To overcome the lack of image analysis tools for whole-organism screening data and to automate the quantification of kidney regeneration post photodamage, we developed a workflow combining image-processing and data-analysis using the open-source software tools FIJI, Ilastik and KNIME. Hence, the workflow enables the analysis of regeneration dynamics and facilitates the identification of specimen with impaired or enhanced regeneration. Ultimately, we expect that workflow components can be directly applied for the analysis of other complex timelapse datasets, and can be adapted for the quantification of growth or migration of other fluorescently labelled tissues.