In the Netherlands, over 12% of the population has chronic kidney damage resulting in about 2000 patients with renal failure each year. Replacement of the kidney function by transplantation is desired, but due to a shortage of donor kidneys, the waiting list for a transplant is long. Extending the criteria that donors must meet can reduce the waiting list, but it is necessary that these organs are still of sufficient quality. Initial studies indicate that using the normothermic machine perfusion (NMP) preservation method results in better transplant outcomes and possibly improves donor kidneys’ quality. The quality of the organ during NMP can be used as a potential biomarker for graft survival. However, what is still missing is a reliable way to test the quality during NMP. Laser speckle contrast imaging (LSCI) is a non-invasive, continuous, real-time imaging technique that can visualize tissue perfusion. In this study, a method is designed to visualize the perfusion over the entire surface of normothermic machine-perfused kidneys using LSCI. A three-dimensional (3D) perfusion model is developed based on two-dimensional (2D) LSCI images. This method can then be used to determine the quality of the perfusion of donor kidneys before they are transplanted. A method is designed to obtain LSCI data of porcine kidneys undergoing NMP. Data is recorded during the first 100 minutes of NMP to evaluate the relationship between renal arterial blood flow and perfusion. The kidneys are then placed in six different positions from which LSCI data is collected. Using shape from silhouettes, a 3D model is made from each kidney. The 2D LSCI data is given depth using the 3D model by assigning each pixel a 3D coordinate. The perfusion model is validated by comparing the perfusion model for the situation where no ischemia is present in the kidney and the situation where ischemia is present in the kidney.  The designed method and setup made it possible to obtain perfusion data over the vast majority of the surface of the kidneys. Further, the results show a positive linear correlation between measured perfusion and arterial blood flow in each kidney. With the collected perfusion data, a 3D visualization was made. 3D models from all kidneys could be used for this. The 3D visualization is represented as a point cloud and allows for easy and fast viewing of the perfusion over the entire surface. Validating the model with induced ischemia showed that the 3D visualization can indicate significant perfusion differences caused by ischemia. This makes LSCI a promising method for determining perfusion quality.