To address the issues of significant cross-sectional distortion in the bent segment, low forming accuracy, and low production efficiency in the manual bending process of micro heat pipes, this paper proposes an automatic rotary press-bending method based on 3D geometric feature extraction and point cloud fitting compensation. The objective is to achieve intelligent generation of bending process parameters and high‑precision forming control, thereby enhancing the manufacturing efficiency of micro heat pipes while preserving their heat transfer characteristics. First, key geometric feature parameters are extracted by parsing the 3D model of the micro heat pipe using boundary representation, and case-based reasoning technology is applied to automatically generate pre-bending process parameters. The bending machine then completes the press-bending formation. Next, 3D point cloud data of the formed micro heat pipe is acquired via scanning. After preprocessing including denoising and simplification, the actual geometric dimensions are obtained through orientation, segmentation, and axis fitting. Finally, the actual dimensions are compared with the target dimensions, and the forming process parameters are corrected based on the differences. Experimental results show that the proposed method can automatically generate press-bending process parameters, achieving dimensional errors ≤ 0.5 mm and angular errors ≤ 0.5°. Compared with manually determined parameters, this method reduces the parameter determination time by over 75%. This study provides a new approach for efficient and precise press-bending formation of micro heat pipes.