Abstract Solving the inverse problem of nanoparticle characterization has the potential to advance science and benefit society. While considerable progress has been made within a framework based on the scattering of surface plasmon-polaritons, an aspect not heretofore considered is the quantification of uncertainty in the estimation of a nanoparticle characteristic. Therefore, the present article offers a technique by which an investigator may augment an estimate of a nanoparticle characteristic with a companion “credible interval”. Analogous to the familiar confidence interval but arising from within the Bayesian statistical paradigm, a credible interval allows the investigator to make a statement such as “the nanoparticle diameter lies between 36 and 48 nm with 95% probability” instead of merely “the nanoparticle diameter is estimated to be 42 nm”. Our technique may even be applied outside of the surface plasmon-polariton scattering framework, as long as the investigator specifies his/her prior beliefs about the nanoparticle characteristic and indicates which potential outcomes are likely or unlikely in whatever experiment he/she designs to estimate the nanoparticle characteristic. Two numerical studies illustrate the implementation and performance of our technique in constructing ranges of likely values for nanoparticle diameters and agglomeration levels, respectively.