In this paper, a meta-structure of piano accompaniment figure (meta-structure for short) is proposed to harmonize a melodic piece of music so as to construct a multi-voice music. Here we approach melody harmonization with piano accompaniment as a machine learning task in a probabilistic framework. A series of piano accompaniment figures are collected from the massive existing sample scores and converted into a set of meta-structure. After the procedure of samples training, a model is formulated to generate a proper piano accompaniment figure for a harmonizing unit in the context. This model is flexible in harmonizing a melody with piano accompaniment. The experimental results are evaluated and discussed. In this paper, a meta-structure of piano accompaniment figure (meta-structure for short) is proposed to harmonize a melodic piece of music so as to construct a multi-voice music. Here we approach melody harmonization with piano accompaniment as a machine learning A series of piano accompaniment figures are collected from the massive existing sample scores and converted into a set of meta-structure. After the procedure of samples training, a model is formulated to generate a proper piano accompaniment figure for a harmonizing unit in the context. This model is flexible in harmonizing a melody with piano accompaniment. The experimental results are evaluated and discussed.