The study has developed a geometrical toolset to calculate biometric parameters of large growing trees using distorted images captured by a digital camera. This toolset focuses on determining a variable scaling factor that accounts for the camera’s inclined position relative to the horizon. An algorithm for the software and an associated online web service has been created. For measurements, a standard ruler, such as one that is 1,000 mm long, is placed on the tree trunk at a height of 1.3 m from the base. The distance from the lens to the standard is measured with an accuracy of ±0.2%. The trunk thickness (DBH) measurement accuracy is not below 1 mm per 1 pixel. This analysis derives from the similarity of triangles in the camera’s field of view, specifically from the lens to the tree trunk and from the lens to the image sensor. The parameters of the digital image are essential, particularly the lens’s focal length varying from 20 mm to 200 mm. Similar but more complex geometric proportions are applied, in case the trunk is vertical. The process involves considering the tilt of the camera matrix to the horizon, and the slope from the lens to the standard reference point. Key factors include the predetermined distance and slope from the lens to the standard on the trunk, along with the parameters of the digital image, particularly the lens’s focal length, typically ranging from 6 to 10 mm. An online web service is offered to perform the relevant measurements and calculations. The software facilitates automatic calculations and generates a data array containing scaling factors corresponding to various height levels from the tree base. Simultaneously, a Visual Basic command array is produced to mark the digital image of the tree at these height levels, complete with scaling factor indicators. This method enables the measurement of trunk thickness at the required heights in pixels, which can then be converted into millimeters. The measurement accuracy is from 6 to 10 millimeters per pixel. The collected data is subsequently organized into a table in Excel. Then, the cross-sectional areas of all trunk segments and their respective volumes were calculated. The total trunk volume is determined by summing the volumes of these segments. The proposed methodology is original, has no prototypes, and may be suitable for practical application.