Maximum-likelihood (ML) methods are more and more used to infer phylogenies, because of their high level of accruracy. I'll present the main components and features of this approach: 1) preamble, basic principle and properties; 2) ML distance estimation; 3) tree likelihood computation via the pruning algorithm; 4) heuristics to search the tree space; 5) simulation results, computing times and topological accuracy compared to other methods; 6) approximate likelihood ratio test for branch supports.