Given a sequence (C, T) = (C, T 1, T 2, . . .) of real-valued random variables with T j ≥ 0 for all j ≥ 1 and almost surely finite N = sup{j ≥ 1 : T j > 0}, the smoothing transform associated with (C, T), defined on the set \({\mathcal{P}(\mathbb R)}\) of probability distributions on the real line, maps an element \({P \in \mathcal{P}(\mathbb R)}\) to the law of \({C + \sum_{j \geq 1} T_j X_j}\) , where X 1, X 2, . . . is a sequence of i.i.d. random variables independent of (C, T) and with distribution P. We study the fixed points of the smoothing transform, that is, the solutions to the stochastic fixed-point equation \({X_{1} \stackrel {\mathrm{d}}{=}C + \sum_{j \geq 1} T_j X_j}\) . By drawing on recent work by the authors with J.D. Biggins, a full description of the set of solutions is provided under weak assumptions on the sequence (C, T). This solves problems posed by Fill and Janson (Electron Commun Probab 5:77–84, 2000) and Aldous and Bandyopadhyay (Ann Appl Probab 15(2):1047–1110, 2005). Our results include precise characterizations of the sets of solutions to large classes of stochastic fixed-point equations that appear in the asymptotic analysis of divide-and-conquer algorithms, for instance the \({\tt Quicksort}\) equation.