  The rupture of a polymer chain maintained at temperature $T$ under fixed
tension is prototypical to a wide array of systems failing under constant
external strain and random perturbations. Past research focused on analytic and
numerical studies of the mean rate of collapse of such a chain. Surprisingly,
an analytic calculation of the probability distribution function (PDF) of
collapse rates appears to be lacking. Since rare events of rapid collapse can
be important and even catastrophic, we present here a theory of this
distribution, with a stress on its tail of fast rates. We show that the tail of
the PDF is a power law with a {\em universal} exponent that is theoretically
determined. Extensive numerics validate the offered theory. Lessons pertaining
to other problems of the same type are drawn.
