Your comments seem somewhat contradictory:
My interest is in an answer possessing utility in the sciences or engineering fields.
I'm deeply interested in mathematics and I want to know why the Lebesgue integral has supplanted the Riemann integral as the integral par excellence in mathematics. Surely there's some compelling reason.
The first quote suggests that you only care about applications of Lebesgue integration and measure theory, while the second quote suggests that you are interested in the pure-mathematical perspective.
Anyway, I will offer answers to both, as a non-expert:
If you use somewhat advanced probability theory (stochastic processes, perhaps particularly continuous-time ones) in your applied math, then measure theory makes probability theory a more coherent subject. The measure-theoretic perspective does away with the discrete-vs.-continuous dichotomy of random variables and is (in my experience), basically mandatory for understanding basic properties of something like Brownian motion.
From the pure-mathematical perspective, I think the standard answer often strongly implies that the Lebesgue integral is superior because it (mostly) generalizes the Riemann integral, and lets you integrate weirder functions like the Dirichlet function. There are also spaces of functions associated with the Lebesgue integral that are "complete", which is a nice property in analysis. However, I will offer another answer which is that the Lebesgue integral is just another kind of integral, better in some cases and worse in others. There are a number of different types of derivatives, so if you're interested in analysis, it's not too strange that there might be different types of integrals you should learn.
Lastly, the pure-mathematical reasons to study measure theory are basically, i) you think it's cool, and/or ii) if you think any more advanced analysis is cool, like functional analysis or PDEs, then measure theory is probably mandatory.