The invention provides a mahalanobis distance laser cladding optimization process based on a principal component analysis method. The method is characterized by firstly designing and performing an orthogonal test according to requirements; collecting experimental data and establishing a sample matrix; carrying out the dimension reduction processing on the multi-dimensional variable system by adopting a principal component analysis method; wherein each variable reflects the original information amount and is linearly irrelevant to each other, calculating distances between each experimental scheme and the optimal solution and between each experimental scheme and the worst solution by adopting a Markov distance approximate ideal solution, and sequencing the experimental schemes and the worstsolution according to the relative closeness between the experimental schemes and the positive ideal solution scheme to obtain a current optimal scheme; and sorting the average close degrees under different process parameters to obtain an optimized process parameter combination. The principal component analysis (PCA)-based Mahalanobis distance TOPSIS method is applied to a laser cladding experiment, multiple process targets can be optimized at the same time, a cladding layer with good comprehensive performance is obtained, and the goodness of fit with actual requirements is higher.