Waterjet-guided laser machining is a novel process used for precision cutting and drilling of various materials and geometries. There are many noise factors in the process affecting the laser beam characteristics, namely the effective cutting length and laser power in the waterjet. Although these variables are mainly set by the laser and waterjet parameters, uncontrollable factors result in variations. Prediction methods such as regression or artificial neural networks provide accuracy up to a certain extent. Measuring the exact values of the laser beam characteristics is crucial for process planning and selection of the machining parameters, such as stand-off distance and number of cycles. In this study, two different real-time measurement methods related to image processing and acoustic signal processing are proposed, both of which provide instantaneous readings for the laser beam characteristics in a waterjet-guided laser machine.