Nowadays, enzymes can be efficiently identified and screened from metagenomic resources or mutant libraries. A set of a few hundred new enzymes can be found using a simple substrate within few months. Hence, the establishment of collections of enzymes is no longer a big hurdle. However, a key problem is the relatively low rate of positive hits and that a timeline of several years from the identification of a gene to the development of a process is the reality rather than the exception. Major problems are related to the time-consuming and cost-intensive screening process that only very few enzymes finally pass. Accessing to the highest possible enzyme and mutant diversity by different, but complementary approaches is increasingly important. The aim of this review is to deliver state-of-art status of traditional and novel screening protocols for targeting lipases, esterases and phospholipases of industrial relevance, and that can be applied at high throughput scale (HTS) for at least 200 distinct substrates, at a speed of more than 105 – 108 clones/day. We also review fine-tuning sequence analysis pipelines and in silico tools, which can further improve enzyme selection by an unprecedent speed (up to 1030 enzymes). If the hit rate in an enzyme collection could be increased by HTS approaches, it can be expected that also the very further expensive and time-consuming enzyme optimization phase could be significantly shortened, as the processes of enzyme-candidate selection by such methods can be adapted to conditions most likely similar to the ones needed at industrial scale.