Objective Aiming at the phenomenon of the increasingly close connection between economy and society and meteorological changes the complex characteristics of meteorological data and high-quality economic development data and the problem of insufficient prediction accuracy of the traditional model this study proposed to carry out the prediction of meteorological factors on the high-quality development of the economy from the perspective of the correlation between meteorology and high-quality development of the economy by statistical methods. Methods Gaussian process regression model has strong adaptability to highly nonlinear regression problems and it can also adaptively obtain the optimal hyperparameters and give probabilistic prediction results. Therefore the Gaussian process regression model was introduced into the prediction of meteorological factors on high-quality economic development. Seven different kernel functions were used the optimal hyperparameters were trained and the best model kernel function and corresponding parameters were selected by comparing the mean square errors. Results A Gaussian process regression GPR model was constructed based on the historical observation data of meteorology and high-quality economic development in Chongqing. The results obtained from the analysis of prediction errors showed that compared with K-proximity regression model and support vector regression model the GPR model which used the hybrid kernel formed by the combination of constant kernel with a parameter of 8. 091 and RBF kernel with scaling parameter of 9. 454 5 as the best kernel function had a lower error. The absolute error of the y-value predicted by the GPR model was 0. 548 at the maximum and 0. 094 at the minimum which was more accurate. The comparison between the real values of the model and the predicted values showed a relatively good fitting effect. Conclusion The GPR model is excellent for the forecast analysis of meteorological factors on high-quality economic development. For the characteristics of the relationship between meteorology and high-quality economic development index effective suggestions including strengthening the meteorological forecast improving the utilization efficiency and making accurate predictions are put forward.