The thing I've seen with estimation practice last I researched it is, it works best if you can calibrate. That's something an established shop can do by extrapolating from their previous work, but it is also often as simple as "This other team took 7 months to do a similar thing. Therefore we will also take 7 months." An estimate like that is usually only wrong by days-to-weeks, since it encompasses all phases, eliminating the fudge-factor, unknown-unknowns and wishful-thinking aspects.

When it takes much longer, it's almost always due to design issues or political issues that create design issues. When the design is well-understood(and prototyping is hugely important to finishing design ASAP) the implementation goes smoothly. When stakeholders take turns stirring the pot to "make their mark", it goes haywire very quickly.

Expert committee estimation (most commonly the Delphi method is cited) is one are that has shown improved estimation accuracy:

https://www.computing.dcu.ie/~renaat/ca421/LWu1.html

The SEI recognizing the weaknesses of expert judgement estimates has layered on QUELCE which applies Monte Carlo simulations to the estimates:

https://www.sei.cmu.edu/research-capabilities/all-work/displ...

Note that QUELCE is an ongoing research methodology without a lot of data available about its effectiveness. But it says something that this is a very active research area in 2018. If it were a solved problem I’d not think Monte Carlo distributions would be valuable.