The invention provides a 4G user loss early warning method and system based on multi-dimensional combined variables, and the method comprises the steps of obtaining a significant index which influences user loss, wherein the significant index comprises a consumption transaction index, a competitor influence index, an abnormal silence index, a remote roaming index, and a use time index; and calculating a loss probability through the trained user loss early warning model, and if the loss probability is greater than a set threshold, determining that the user is a to-be-lost user, and concluding into five influence dimensions, namely a consumption transaction index, a competitor influence index, an abnormal silence index, a remote roaming index and a use time index. A principal component analysis idea is applied to recombine and integrate a plurality of variables in a dimension into a modeling index with the maximum information value, so that the problems of collinearity of an estimation equation and loss of original data information are solved, the value of a service index is maximized, and the data prediction accuracy is improved.