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Purpose: Our objective is to apply an improved statistical global model ofbeta^- decay half-life systematics [1] generated by machine-learning techniquesto the prediction of beta half-lives relevant to r-process nuclei. The primaryaim of this application is to complement existing r-process-clock andmatter-flow studies, thereby providing additional theoretical support for theplanning of future activities of the world's network of rare-isotopelaboratories.  Results: Results are presented for nuclides situated on the r-ladders atN=50, 82, and 126 where abundances peak, as well as for nuclides that affectabundances between peaks or may be relevant to r-processes under differentastrophysical scenarios. The half-lives of some of the targeted neutron-richnuclides have either been recently measured or will be accessible atrare-isotope laboratories in the relatively near future. The results of ourlarge-scale data-driven half-life calculations (generated by a "theory-thin"global statistical model) are compared to available experimental data,including recent measurements on very neutron-rich nuclei along an r-processpath far from the valley of $\beta$ stability. Comparison is also made withcorresponding results from traditional global models derived bysemi-phenomenological "theory-thick" approaches.

Statistical Global Model of beta- Half-lives and r-Process Nucleosynthesis