Probability contributes 2-3 questions annually in JEE Main, spanning classical probability, conditional probability, Bayes' theorem, and binomial distribution. The chapter requires both counting skills and probability framework identification.

Classical probability uses P(A) = n$\frac{A}{n}$(S) for equally likely outcomes. The complement rule P(A') = 1 - P(A) is the fastest approach for "at least one" problems. The addition rule P(A union B) = P(A) + P(B) - P(A intersect B) handles unions, simplifying for mutually exclusive events where the intersection is zero.

Conditional probability P(A|B) = P$\frac{A intersect B}{P}$(B) restricts the sample space. Independence requires P(A intersect B) = P(A)*P(B). A critical distinction: mutually exclusive events with non-zero probabilities are NEVER independent.

Bayes' theorem reverses conditional probability: P($B_i$|A) = P(A|$B_i$)*P$\frac{B_i}{P}$(A), using total probability in the denominator. Common JEE applications include defective items from multiple machines and ball-drawing from multiple bags.

The binomial distribution B(n,p) models n independent trials with P(X=r) = C(n,r)*$p^r$*q^(n-r). Mean = np, Variance = npq. The mode lies near (n+1)p.

Key problem-solving strategy: first identify the probability framework (classical counting, conditional, Bayes', or binomial), then apply the appropriate formula systematically.