Retina vessel segmentation is a challenging task that concerns scientists for many years. Vasculature gives us information for possible diseases like diabetic retinopathy, hypertension etc. Different algorithms have been developed using matched filters, pattern recognition techniques and scale-space techniques, which present reliable results. Currently the most challenging task is the estimation of vessels’ width of the whole retina vasculature. At this article, a method for the calculation of vessels’ minimum, maximum and mean width of every single vessel that we obtain from the already segmented binary image is proposed. Having this information we can evaluate the cardiovascular functionality, such as volumetric flow, flow velocity, and tension at the vessels’ walls during blood circulation. The proposed algorithm tracks the bifurcation points of the whole vasculature using the skeleton of the initial image and uses a decision making technique to decide which vessel to cross each time. Finally the algorithm crosses the vessel pixel-by-pixel and calculates the width until the end of the vessel. The whole procedure is automatic and we can see the remaining skeleton in our screen, after estimating a single vessel’s width, since this vessel disappears from the image. Each vessel’s width is calculated with pixel accuracy.