Numerical model was developed to simulate the microsegregation and phase transformation for an Fe-based multicomponent alloy with peritectic transformation. The present model was based on the simplest one-dimensional free boundary problem and assumed the local equilibrium condition at the interface. In addition, the model was coupled with thermodynamic calculation software (ChemAPP) in order to calculate equilibrium concentration at an interface. As the calculation region, the transverse and longitudinal cross section of columnar dendrite was approximated by a star shape, assuming dendrite envelope. The validity of the present model was evaluated by comparing with the analytical models and experimental data. In the comparison with the analytical models, which are lever rule, Gulliver–Scheil model and Clyne–Kurz model, the calculated results were close to the curve of lever rule for Fe–C binary alloy, and were close to the curve of Gulliver–Scheil model for Fe–Mn binary alloy. For both alloys, the calculated results were in good agreement with the curves of Clyne–Kurz model. The relationship between peritectic temperature range and carbon content was calculated for Fe–C binary alloy and compared with the result of a model by Fredriksson et al. [H. Fredriksson et al.: Metal Science, 16 (1982), 575]. The calculated result was in great agreement with their one. Also, the peritectic temperature range for peritectic content was not always the maximum, and the carbon content slightly shifted to hyper-peritectic side as the cooling rate became higher. For Fe–C–Mn–Si–P–Mo alloy, we calculated microsegregation and peritectic transformation, and compared with the experimental data reported by Ueshima et al. [Y. Ueshima et al.: Tetsu-to-Hagané, 73 (1987), 1551]. Temperatures of δ/γ transformation and γ-solidification decreased by adding to molybdenum, and these results were close to those of Ueshima et al. Also, the distributions of manganese, phosphorus and molybdenum calculated by the present model were in essential agreement with those of their experimental data.