Forecasting pharmaceutical market dynamics characterized by pronounced seasonal fluctuations remains a methodological challenge for healthcare planning systems. This study proposes a methodology for forecasting pharmaceutical market indicators using a seasonality index, demonstrated on the example of anthelmintic drugs. Monthly data from the Drug Audit database covering the period 2009–2024 were analyzed, and forecast estimates were developed up to 2031 using a multiplicative time series model and a scenario-based approach including baseline, optimistic, and pessimistic scenarios. To our knowledge, limited studies have applied seasonality-index-based forecasting to the pharmaceutical market of anthelmintic drugs. The methodology was tested both at the level of individual International Nonproprietary Names (albendazole, mebendazole, and pyrantel) and at the level of the aggregated anthelmintic market. The results demonstrate that incorporating seasonality indices improves the reliability of demand forecasting and supports evidence-based pharmaceutical supply planning and decision-making.