Yes, you could just repeatedly apply the approach in the other answer; if you have
$$P(A\cup B)=P(A)+P(B)-P(A\cap B)$$
then it follows from your though that
$$P(A\cup B\cup C)=P(A\cup B) + P(C) - P((A\cup B)\cap C)$$
and as $(A\cup B)\cap C=(A\cap C)\cup (B\cap C)$ we can simplify to
$$P(A\cup B\cup C)=P(A\cup B) + P(C) - P((A\cap C)\cup (B\cap C))$$
then, applying the approach to the two unions on the left:
$$P(A\cup B\cup C)=(P(A)+P(B)-P(A\cup B)) + P(C) - (P(A\cap C) + P(B\cap C) + P(A\cap C \cap B \cap C))$$
or more cleanly written
$$P(A\cup B\cup C)=P(A)+P(B)+P(C)-P(A\cap B)-P(A\cap C)-P(B\cap C) +P(A\cap B\cap C).$$
You could certainly continue to apply this process, however it will become tedious before too long, as each addition term of the union about doubles the number of terms in the expansion. However, a simple generalization does exist, called the inclusion-exclusion principle. Essentially, what it says is that to calculate $P(A_1\cup A_2 \cup A_3 \cup \ldots)$, you sum up the individual probabilities $P(A_i)$ for each $A$, then subtract the probabilities $P(A_i\cap A_j)$ for distinct $i$ and $j$ (the probabilities of any two events happening), then add all $P(A_i\cap A_j \cap A_k)$ into the sum, subtract $P(A_i\cap A_j\cap A_k \cap A_s)$ and so on. The Wikipedia page illustrates it fairly well (though it uses cardinality of sets - but it applies more widely to any measure, of which probability and cardinality are examples)