For a Poisson distribution, the probability mass function is given by:
\[
P(X = k) = \frac{\lambda^k e^{-\lambda}}{k!}
\]
where \( \lambda \) is the mean of the distribution, and \( k \) is the value for which we want to find the probability.
Given that \( P(X = 1) = P(X = 2) \), we can set up the equation:
\[
\frac{\lambda^1 e^{-\lambda}}{1!} = \frac{\lambda^2 e^{-\lambda}}{2!}
\]
Simplifying the equation:
\[
\lambda = \frac{\lambda^2}{2}
\]
Solving for \( \lambda \):
\[
\lambda = 2.
\]
Now that we have \( \lambda = 2 \), we can calculate \( P(X = 3) \) using the Poisson distribution formula:
\[
P(X = 3) = \frac{2^3 e^{-2}}{3!} = \frac{8 e^{-2}}{6}.
\]
Approximating \( e^{-2} \approx 0.1353 \), we get:
\[
P(X = 3) = \frac{8 \times 0.1353}{6} \approx 0.1804.
\]
Thus, the value of \( \text{Prob}(X = 3) \) is \(0.18 \).