Considering the influence of stochastic load growth in voltage stability load margin computation, a probabilistic voltage stability assessment method of large power grid is proposed. The improved K-means clustering algorithm is used to classify the load types according to historical load data. Then the expectation value of stochastic load growth is defined based on load forecasting and load classification results. According to the probability distributions of load growth direction, the samples are generated by the Latin Hypercube Sampling method. The continuation power flow is utilized for computing load margin of each sample. The numerical results of probabilistic voltage stability assessment in a large power grid of China show that the proposed method is effective and practical. This work is supported by National Natural Science Foundation of China (No. 51577049) and Science and Technology Project of China Southern Power Grid Company (No. KYKJXM00000001) “Research and Development of Advanced Function on Static Voltage Security Assessment for AC/DC Power Grids”.