1. This software is made just for scientific research, so I don’t promise whether the calculated results are correct,because, as you know,there are many algorithms for gravity inversion, and because of the nonuniqueness of gravity inversion. 2. This software just can be used in Windows platform, and Matlab2016b is necessary, no test for other versions of Matlab. Please double-click the "DenInv3D.exe" to run directly, it is just only one file of EXE, no installation. 3. I don’t send you the help file, because it is in Chinese. 4. You can use the right-button of mouse to open/save the model in the modeling table area, to open file in file list area. And also, you can use the Menu to open or save file. 5. For first time to calculate, you should make a model,and open the observed data(best in ASCII GRD format of Golden Software Surfer). The software calculate the kernel function automatically,you can save the kernel function to a file to save time for next time. Z axis is vertical down(take the downward direction as positive). 6. About the format of initial model file, it is TXT or DAT with one column for initial density if you want to use the function of initial model, the sequence (order) is the same with the inverted result of density, you can try to save a result to find the order. 7. The unit is m (metre) for coordinate, distance or depth , including the modelled and observed data. The unit is mGal for gravity, E for gravitational gradient,and g/cm^3 for density. 8. Please tell me about the bug of software,don't hesitate to contact me if you have any question. references: (1)Yu Tian, Xiaoping Ke,Yong Wang. DenInv3D:A geophysical software for three-dimensional density inversion of gravity field data. Journal of Geophysics and Engineering, 2018,15(2):354-365.https://doi.org/10.1088/1742-2140/aa8caf (2)Xiaoping Ke, Muge Tian, Dongliang Guan,Yong Wang, Hongling Shi. Gravitational gradients derived from GOCE and density structures beneath the North China Craton. Journal of Asian Earth Sciences, 2019,174:152-166. https://doi.org/10.1016/j.jseaes.2018.12.002