"Fillers", example "um" in English, have been linked to the "Feeling of Another's Knowing (FOAK)" or the listener's perception of a speaker's expressed confidence. Yet, in Spoken Language Processing (SLP) they remain unexplored, or overlooked as noise. We introduce a new and challenging task, that is the prediction of FOAK, which we think has widespread applicability, given the increasing popularity of automatic processing of educational and job interviews, reviews and speeches. We design a set of filler features based on linguistic literature, and investigate their potential in FOAK prediction. We show that the integration of information related to implicature meanings allows an improvement in the FOAK model and that the different functions of fillers are differently correlated with confidence.