Cholinesterase enzymes play a pivotal role in hydrolyzing acetylcholine, a neurotransmitter crucial for memory and cognition, into its components, acetic acid, and choline. A primary approach in addressing Alzheimer's disease symptoms is by inhibiting the action of these enzymes. With this context, our study embarked on a mission to pinpoint potential Cholinesterase (ChE) inhibitors using a comprehensive computational methodology. A total of 49 phytoconstituents derived from Cannabis sativa L underwent in silico screening via molecular docking, pharmacokinetic and pharmacotoxicological analysis, to evaluate their ability to inhibit cholinesterase enzymes. Out of these, two specific compounds, namely tetrahydrocannabivarin and Δ-9-tetrahydrocannabinol, belonging to cannabinoids, stood out as prospective therapeutic agents against Alzheimer's due to their potential as cholinesterase inhibitors. These candidates showcased commendable binding affinities with the cholinesterase enzymes, highlighting their interaction with essential enzymatic residues. They were predicted to exhibit greater binding affinities than Rivastigmine and Galantamine. Their ADMET assessments further classified them as viable oral pharmaceutical drugs. They are not expected to induce any mutagenic or hepatotoxic effects and cannot produce skin sensitization. In addition, these phytoconstituents are predicted to be BBB permeable and can reach the central nervous system (CNS) and exert their therapeutic effects. To delve deeper, we explored molecular dynamics (MD) simulations to examine the stability of the complex formed between the best candidate (Δ-9-tetrahydrocannabinol) and the target proteins under simulated biological conditions. The MD study affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes. Our research outcomes provide valuable insights, offering a clear direction for the pharmaceutical sector in the pursuit of effective anti-Alzheimer treatments.