The invention discloses an electric charge sensitivity assessment method based on logistic regression. According to the method, electric charge sensitivity models are respectively established for high-voltage users, low-voltage non-resident customers, and resident customers by regarding customer sensitivity as the entry point. The main steps comprise: collecting modeling indexes from a plurality of dimensions including customer basic information, electricity consumption information, and payment information etc., screening variables by employing information values (IV) and related coefficients, grouping the variables based on the optimal grouping algorithm and the optimal clustering algorithm, performing conversion of weight of evidence (WOE), establishing the customer electric charge sensitivity assessment model by employing a logistic regression algorithm, constructing a standard scoring card which is easily understood and implemented according to model parameter estimation values, and finally determining the weights of the variables through an advantage analysis method. According to the method, data support is provided for development of accurate marketing and differentiated service by departments of electric power marketing and customer service through recognition of customers with high electric charge sensitivity, the overall satisfaction degree of the customers is improved, and the customer perception is improved.