Here are a couple of "proofs" of Stirling's formula. They are quite elegant (in my opinion), but not rigorous. On could write down a real proof from these, but as they rely on some hidden machinery, the result would be quite heavy.
1) A probabilistic non-proof
We start from the expression $e^{-n} n^n/n!$, of which we want to find an equivalent. Let us fix $n$, and let $Y$ be a random variable with a Poisson distribution of parameter $n$. By definition, for any integer $k$, we have $\mathbb{P} (Y=k) = e^{-n} n^k/k!$. If we take $k=n$, we get $\mathbb{P} (Y=n) = e^{-n} n^n/n!$. The sum of $n$ independent random variables with a Poisson distribution of parameter $1$ has a Poisson distribution of parameter $n$; so let us take a sequence $(X_k)$ of i.i.d. random variables with a Poisson distribution of parameter $1$. Note that $\mathbb{E} (X_0) = 1$. We have:
$$\mathbb{P} \left( \sum_{k=0}^{n-1} (X_k - \mathbb{E} (X_k)) = 0 \right) = \frac{e^{-n} n^n}{n!}.$$
In other words, $e^{-n} n^n/n!$ is the probability that a centered random walk with Poissonnian steps of parameter $1$ is in $0$ at time $n$. We have tools to estimates such quantities, namely local central limit theorems. They assert that:
$$\frac{e^{-n} n^n}{n!} = \mathbb{P} \left( \sum_{k=0}^{n-1} (X_k - \mathbb{E} (X_k)) = 0 \right) \sim \frac{1}{\sqrt{2 \pi n \text{Var} (X_0)}},$$
a formula which is closely liked with Gauss integral and diffusion processes. Since the variance of $X_0$ is $1$, we get:
$$n! \sim \sqrt{2 \pi n} n^n e^{-n}.$$
The catch is of course that the local central limit theorems are in no way elementary results (except for the simple random walks, and that is if you already know Stirling's formula...). The methods I know to prove such results involve Tauberian theorems and residue analysis. In some way, this probabilistic stuff is a way to disguise more classical approaches (in my defense, if all you have is a hammer, everything looks like a nail).
I think one could get higher order terms for Stirling's formula by computing more precise asymptotics for Green's function in $0$, which requires the knowledge of higher moments for the Poisson distribution. Note that the generating function for a Poisson distribution of parameter $1$ is:
$$\mathbb{E} (e^{t X_0}) = e^{e^t-1},$$
and this "exponential of exponential" will appear again in a moment.
2) A generating functions non-proof
If you want to apply analytic methods to problems related to sequences, generating functions are a very useful tool. Alas, the series $\sum_{n \geq 0} n! z^n$ is not convergent for non-zero values of $z$. Instead, we shall work with:
$$e^z = \sum_{n \geq 0} \frac{z^n}{n!};$$
we are lucky, as this generating function is well-known. Let $\gamma$ be a simple loop around $0$ in the complex plane, oriented counter-clockwise. Let us fix some non-negative integer $n$. By Cauchy's formula,
$$\frac{1}{n!} = \frac{1}{n!} \frac{\text{d} e^z}{\text{d} z}_{|_0} = \frac{1}{2 \pi i} \oint_\gamma \frac{e^z}{z^{n+1}} \text{d} z.$$
We choose for $\gamma$ the circle of radius $n$ around $0$, with its natural parametrization $z (t) = n e^{it}$:
$$\frac{1}{n!} = \frac{1}{2 \pi i} \int_{- \pi}^{\pi} \frac{e^{n e^{it}}}{n^{n+1} e^{(n+1)it}} nie^{it} \text{d} t = \frac{e^n}{2 \pi n^n} \oint_{- \pi}^{\pi} e^{n (e^{it}-it-1)} \text{d} t = \frac{e^n}{2 \pi \sqrt{n} n^n} \int_{- \pi \sqrt{n}}^{\pi \sqrt{n}} e^{n \left(e^{\frac{i\theta}{\sqrt{n}}}-\frac{i\theta}{\sqrt{n}}-1\right)} \text{d} \theta,$$
where $\theta =t \sqrt{n}$. Hitherto, we have an exact formula; note that we meet again the "exponential of exponential". Now comes the leap of faith. For $x$ close to $0$, the value of $e^x-x-1$ is roughly $x^2/2$. Moreover, the bounds of the integral get close to $- \infty$ and $ \infty$. Hence, for large $n$, we have:
$$\frac{1}{n!} \sim \frac{e^n}{2 \pi \sqrt{n} n^n} \int_{- \infty}^{+ \infty} e^{\frac{n}{2} \left(\frac{i\theta}{\sqrt{n}}\right)^2} \text{d} \theta = \frac{e^n}{2 \pi \sqrt{n} n^n} \int_{- \infty}^{+ \infty} e^{-\frac{\theta^2}{2}} \text{d} \theta = \frac{e^n}{\sqrt{2 \pi n} n^n}.$$
Of course, it is not at all trivial to prove that the equivalents we took are rigorous. Indeed, if one apply this method to bad generating functions (e.g. $(1-z)^{-1}$), they can get false results. However, this can be done for some admissible functions, and the exponential is one of them.
I have learnt this method thanks to Don Zagier. It is also explained in Generatingfunctionology, Chapter $5$ (III), where the author credits Hayman. The original reference seems to be A generalisation of Stirling's formula (Hayman, 1956), but I can't read it now.
One of the advantage of this method is that it becomes very easy to get the next terms in the asymptotic expansion of $n!$. You just have to develop further the function $e^x-x-1$ at $0$. Another advantage is that it is quite general, as it can be applied to many other sequences.