This paper investigates the viability of the jump-diffusion model in the oil sector as an alternative to the Black-Scholes framework for option pricing. Using U.S. options data and underlying log-returns of ten major oil-sector firms from 2005 to 2022, the analysis documents both varying implied volatility and systematic mispricing in the Black-Scholes model, particularly for out-of-the-money options. To assess the explanatory power of jump risk, option prices are fitted using a cross-sectional nonlinear least squares procedure under both models, with parameters estimated in rolling windows to capture regime shifts. Crude oil prices are incorporated to contextualize pricing behavior during periods of elevated volatility. The results show modest improvements from the jump-diffusion specification, suggesting that greater gains may come from extended frameworks that combine jumps with stochastic volatility or regime-switching dynamics.