Crossover interference is now known to exist in humans but to date has been ignored in routine genetic mapping because of the computational burden involved. In a recent paper by Weeks et al. [Hum. Hered. 1993;43:86-97], interference was accounted for by the use of a variety of multilocus feasible map functions and a crossover model of Goldgar and Fain [Am J Hum Genet 1988;43:38-45]. In this paper, we present an alternative approach to incorporating crossover interference into multilocus likelihood computation, by modelling the underlying chiasma process directly using the χ2 model, supplemented by an assumption of no chromatid interference. This procedure was applied to the same CEPH consortium chromosome 10 data set that was analyzed by Weeks et al. A fit to the data was achieved which was significantly better than that offered by the no-interference model, and comparable to the best of the alternatives considered by Weeks et al. We briefly discuss the relative merits of the different models for interference