Targeted identification of poverty alleviation objects is an important precondition to achieve targeted poverty alleviation.Realization of classification and identification of big data,conversion from quantity analysis to quality analysis and change from linear targeting to multi-dimensional targeting are the basis of targeted poverty alleviation.Targeted identification can be achieved by using classification algorithm in big data analysis.Based on the framework of sustainable livelihood analysis,this paper establishes a multi-dimensional poverty index system based on sustainable livelihood from six aspects:human capital,social capital,natural capital,physical capital,financial capital and living environment.Using stochastic forest algorithm to construct a targeted identification model and the data done by Institute of Social Science Survey,Peking University,this paper evaluates the effect of the model for classification and identification of poverty alleviation objects.The results show its validity and reliability.