XML structural joins, which evaluate the containment (ancestor-descendant) relationships between XML elements, are important operations of XML query processing. Estimating structural join size accurately and quickly is thus crucial to the success of XML query plan selection and the query optimization. XML structural joins are essentially complex unequal joins, which render well-known estimation techniques, such as cosine transform, wavelet transform, and sketch, not directly applicable. In this paper, we propose a relation model to capture the structural information of XML data such that the original complex unequal joins are converted to equal joins and those well-known estimation techniques become directly applicable to structural join size estimation. Theoretical analyses and extensive experiments have been performed on these estimation methods. It is shown that the cosine transform requires the least memory and yields the best estimates.