The objective of this study is to study the multi-particle deposition process of cold spray through numerical simulation methods and to use multi-factor coupling to optimize the porosity of Al6061 coating to more accurately characterize the real cold spray deposition process. This study aimed to predict and optimize the porosity of Al6061 coatings using numerical simulation methods. The tasks to be solved are: to nest the multi-particle model established by the Python script in the CEL deposition model to simulate the cold spray deposition process. A multi-parameter function with particle temperature, substrate temperature, and particle velocity as independent variables and Al6061 coating porosity as dependent variables was established. The response surface analysis method was used to predict the optimal spraying parameters and coating porosity of Al6061 coating. The methods used are as follows: optimize the porosity of the coating through multi-factor coupling through response surface analysis; use a multi-particle model established through a Python script to be nested in the CEL deposition model to simulate the deposition process of cold-sprayed Al6061 multi-particles. To characterize the coating porosity more accurately, the average value of multiple groups of samples was taken as the final coating porosity value. Conclusions. the porosity value of Al6061 coating obtained by the prediction model is 1.969%; Under the influence of multi-factor coupling, particle velocity has the greatest impact on the porosity of the Al6061 coating, and the substrate temperature has the least impact. Optimum spraying parameters: particle temperature 649.692K, substrate temperature 536.437K, and particle velocity 672.385m/s. Under the optimal spraying parameters, the porosity value of the Al6061 coating is 1.91875%; The error between the predicted value and the actual value obtained by numerical simulation is only 2.55%.