The invention relates to a power distribution network space load prediction method taking region and load property dual differences into consideration. A conventional space load prediction method does not take influences exerted by regional differences, sample types and quality on load density into consideration, and the applicability is not sufficient. First of all, a full-sample space taking the regional differences into consideration is established, and then, a typical sample is screened by verifying and carefully choosing a load through a typical daily load curve. A region where the load is disposed is clustered through weighted Euclidean distance tolerance, afterwards, a subsample space matching is carried out, a type which the sample belongs to is determined, load density of a plot to be measured is predicted by use of an SVM algorithm, and a total future load amount of the plot is calculated through the load density. The load prediction precision is quite high, and the application is facilitated.