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Population genetic analyses of local ancestry tracts routinely assume that the ancestral admixture process is identical for both parents of an individual, an assumption that may be invalid when considering recent admixture. Here we present Parental Admixture Proportion Inference (PAPI), a Bayesian tool for inferring the admixture proportions and admixture times for each parent of a single admixed individual. PAPI analyzes unphased local ancestry tracts and has two components models: a binomial model that exploits the informativeness of homozygous ancestry regions to infer parental admixture proportions, and a hidden Markov model (HMM) that infers admixture times from tract lengths. Crucially, the HMM employs an approximation to the pedigree crossover dynamics that accounts for unobserved within-ancestry recombination, enabling inference of parental admixture times. We compared the accuracy of PAPI’s admixture proportion estimates with those of ANCESTOR in simulated admixed individuals and found that PAPI outperforms ANCESTOR by an average of 46% in a representative set of simulation scenarios, with PAPI’s estimates deviating from the ground truth by 0.047 on average. Moreover, PAPI’s admixture time estimates were strongly correlated with the ground truth in these simulations (R = 0.76), but have an average downward bias of 1.01 generations that is partly attributable to inaccuracies in local ancestry inference. As an illustration of its utility, we ran PAPI on real African Americans from the PAGE study (N = 5, 786) and found strong evidence of assortative mating by ancestry proportion: couples’ ancestry proportions are closer to each other than expected by chance (P < 10−6), and are highly correlated (R = 0.87). We anticipate that PAPI will be useful in studying the population dynamics of admixture and will also be of interest to individuals seeking to learn about their personal genealogies.