Initial in-situ stress field is an important basis for design and construction of underground engineering, while it is difficult to accurately measure the initial in-situ stress in engineering practice. In order to accurately obtain distribution law pattem of initial geostress field, the immune algorithm combined with BP neural network (IA-BP algorithm) for inversion of initial in-situ stress field is studied. The optimization of BP neural network by immune algorithm is to encode the connection weights and thresholds of BP neural network as antibodies in the immune algorithm. The hybrid algorithm can not only take advantage of the characteristics of immune algorithm as well as the global optimization quick search for the global optimal solution or near optimal solution, and can also adopt BP algorithm to avoid the near optimal and sub-optimal solutions, oscillation on the local optimization, realizing the aim of fast converge of the global optimal solution. The plane slope model and three-dimensional model were constructed by COMSOL respectively to carry out forward analysis and calculation, and the calculated results were taken as “measured values” to conduct inversion analysis of in-situ stress, but the inversion results of IA-BP algorithm were compared with those of PSO-BP and multiple linear regression algorithms. The results show that the inversion error of IA-BP algorithm is smaller under the two-dimensional (2D) slope model. Under the three-dimensional (3D) model, IA-BP algorithm from the measured values and the inversion of the absolute value of relative error between 0% and 10.64% (3.39% on average), for PSO-BP, it is between 1% and 48.39% with average value of 6.93%, for MLR, it is between 0.55% and 121.95% with average of 21.87%. By comparison, it can be known that the overall inversion results of IA-BP algorithm have the highest accuracy. In both 2D and 3D models, the error of the inversion results is smaller than those using the other two. The application of IA-BP intelligent algorithm to the inversion of in-situ stress field can provide technical support for the construction of underground engineering.