Motivation: One essential initial step in the analysis of ancient DNA is to authenticate that the DNA sequencing reads actually are from ancient DNA. This is done by assessing if the reads exhibit typical characteristics of postmortem damage, including cytosine deamination and nicks. We present a novel statistical method implemented in a fast multithreaded program, ngsBriggs, that enables rapid quantification of PMD by estimation of the Briggs ancient damage model parameters (Briggs parameters). Results: Using a multinomial model with maximum likelihood fit, ngsBriggs accurately estimates the parameters of the Briggs model, quantifying the PMD signal from single and double-stranded DNA regions.We extend the original Briggs model to capture PMD signals for contemporary sequencing platforms and show that ngs- Briggs accurately estimates the Briggs parameters across a variety of contamination levels. Classification of reads into ancient or modern reads, for the purpose of decontamination, is significantly more accurate using ngsBriggs than using other methods available. Furthermore, ngsBriggs is substantially faster than other state-of-the-art methods. ngsBriggs offers a practical and accurate method for researchers seeking to authenticate ancient DNA and improve the quality of their data.