Multiple sequence alignment (MSA) generally constitutes the foundation of many bioinformatics studies involving functional, structural, and evolutionary relationship analysis between sequences. As a result of the exponential computational complexity of the exact approach to producing optimal multiple alignments, the majority of state-of-the-art MSA algorithms are designed based on the progressive alignment heuristic. In this chapter, we outline MSAProbs, a parallelized MSA algorithm for protein sequences based on progressive alignment. To achieve high alignment accuracy, this algorithm employs a hybrid combination of a pair hidden Markov model and a partition function to calculate posterior probabilities. Furthermore, we provide some practical advice on the usage of the algorithm.