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Data collection has become one of the most important aspects of daily life. In visualization of data, the number of points determines the clarity of data one can show. One such resource is a point cloud which is a data structure that represents a collection of huge amounts of multidimensional points and is used to store three-dimensional data. LiDAR is an active optical sensing device that provides extremely accurate x, y and z coordinates of the object it is reflected from. It transmits laser beams to a specific object and reflects its movements back to the receiver and analyzes the time span and measures the distance. The information obtained is used to construct a 3D point cloud of reflected obstacles. Also, by adding color information to the point cloud, we can be converted it from 3D to 4D. They are very dense and may be difficult to analyze since the point clouds can store massive amount of data. Handling such amount of data can be difficult and consumes a considerable amount of time for its visualization. We have designed a 3D Annotation Tool which is an application designed to annotate objects in a point cloud scene. We have annotated the objects by drawing 3D bounding boxes around them. The tool we have designed is capable of visualizing point cloud and RGB images together. It makes accessing and understanding of data easy for the observer. We have used PyQt package to design the GUI interface of the tool. PyQt is a Python binding of the cross-platform GUI toolkit Qt, implemented as a Python plugin. It provides features such as loading of point cloud and RGB images, rotation of RGB image, movement in point cloud and many more features.