Here is my approach, although I must admit it's not as slick as the approach developed by @Martin R
Set $p(x)=\frac{1}{\ln(x)}-\frac{1}{\ln^2(x)}$ and pick $\epsilon>0.$
Find $x_0>e$ so that, for any $x\geq x_0$, we have $$\Big|f(x)+\frac{\ln^2(x)}{\ln(x)-1}f'(x)\Big|<\epsilon$$ This means $$\forall x\geq x_0: -\epsilon p(x)e^{\int_{x_0}^xp(s)\mathrm{d}s}< \frac{d}{dx}\Bigg(e^{\int_{x_0}^xp(s)\mathrm{d}s}f(x)\Bigg)<\epsilon p(x)e^{\int_{x_0}^xp(s)\mathrm{d}s}$$ But this is the same as saying $$\forall x\geq x_0: -\epsilon\frac{d}{dx}\Big(e^{\int_{x_0}^xp(s)\mathrm{d}s}\Big)< \frac{d}{dx}\Bigg(e^{\int_{x_0}^xp(s)\mathrm{d}s}f(x)\Bigg)<\epsilon \frac{d}{dx}\Big(e^{\int_{x_0}^xp(s)\mathrm{d}s}\Big)$$ Integrate from $x_0$ to $x$ and get $$\forall x\geq x_0:-\epsilon\Big(e^{\int_{x_0}^xp(s)\mathrm{d}s}-1\Big)<e^{\int_{x_0}^xp(s)\mathrm{d}s}f(x)-f(x_0)<\epsilon\Big(e^{\int_{x_0}^xp(s)\mathrm{d}s}-1\Big)$$ Divide through by $e^{\int_{x_0}^xp(s)\mathrm{d}s}$. $$\forall x\geq x_0: -\epsilon\Big(1-e^{-\int_{x_0}^xp(s)\mathrm{d}s}\Big)<f(x)-f(x_0)e^{-\int_{x_0}^xp(s)\mathrm{d}s}<\epsilon\Big(1-e^{-\int_{x_0}^xp(s)\mathrm{d}s}\Big)$$ It's not hard to show that $\int_{x_0}^{\infty} p(s)\mathrm{d}s=\infty$ so take $x\rightarrow \infty$ and invoke squeeze theorem to see $\Big|\lim_{x\rightarrow \infty}f(x)\Big|<\epsilon$. But $\epsilon>0$ is arbitrary, revealing $f(x)\rightarrow 0$ as $x\rightarrow \infty$