Computational prediction methods for the identification of microRNA (miRNA) target genes benefit from efficient experimental validation strategies. Here we present a large-scale targeted proteomics approach to validate such predicted miRNA targets in Caenorhabditis elegans. Using selected reaction monitoring (SRM), we quantified 161 proteins of interest in extracts from wild-type and let-7 mutant worms. We demonstrate by independent experimental downstream analyses such as genetic interaction, as well as exemplarily performed polysomal profiling and luciferase assays, that validation by targeted proteomics significantly enriches for biologically relevant let-7 interactors. For example, we show that the zinc finger protein ZTF-7 is a bona fide let-7 miRNA target. We also validated a set of predicted miR-58 targets, demonstrating that this approach is adaptable to multiple miRNAs of interest. We propose that targeted mass spectrometry can be applied generally to validate candidate lists generated by computational methods or by large-scale experiments, and that the described strategy can easily be adapted to other organisms.