High-throughput/high-content multiplexed phenotypic (HTS/HCS) screens, such as Cell Painting PLUS (CPP), are employed to identify morphological changes in cells induced by chemical compound treatments or genetic perturbations. These phenotypic screens generate extensive imaging data, from which hundreds to thousands of features describing cellular morphology can be extracted. Open-source software, such as Cell Profiler and KNIME Analytics Platform, provides useful tools for image analysis and data processing. In this chapter, we present a comprehensive Cell Profiler pipeline for the analysis of images generated using the Cell Painting PLUS method. The image analysis procedure starts with illumination correction, followed by image registration using 4i stitcher software developed in our laboratory to combine images scanned from different staining cycles. Subsequently, cell region segmentation and feature extraction are performed. The approximately 3000 extracted features are processed via the KNIME Analytics Platform, which relies primarily on visual programming elements to minimize the need for coding expertise. This process includes normalization and benchmark dose modeling. The responsive features or feature categories are visualized using an “accumulation plot” and a “magnitude plot,” allowing users of CPP to summarize the most potentially affected organelle by the tested compound or genetic perturbation.